共查询到20条相似文献,搜索用时 656 毫秒
1.
Wan D. Bae Shayma Alkobaisi Seon Ho Kim Sada Narayanappa Cyrus Shahabi 《GeoInformatica》2009,13(4):483-514
As Geographic Information Systems (GIS) technologies have evolved, more and more GIS applications and geospatial data are
available on the web. Spatial objects in a given query range can be retrieved using spatial range query − one of the most
widely used query types in GIS and spatial databases. However, it can be challenging to retrieve these data from various web
applications where access to the data is only possible through restrictive web interfaces that support certain types of queries.
A typical scenario is the existence of numerous business web sites that provide their branch locations through a limited “nearest
location” web interface. For example, a chain restaurant’s web site such as McDonalds can be queried to find some of the closest
locations of its branches to the user’s home address. However, even though the site has the location data of all restaurants
in, for example, the state of California, it is difficult to retrieve the entire data set efficiently due to its restrictive
web interface. Considering that k-Nearest Neighbor (k-NN) search is one of the most popular web interfaces in accessing spatial data on the web, this paper investigates the problem
of retrieving geospatial data from the web for a given spatial range query using only k-NN searches. Based on the classification of k-NN interfaces on the web, we propose a set of range query algorithms to completely cover the rectangular shape of the query
range (completeness) while minimizing the number of k-NN searches as possible (efficiency). We evaluated the efficiency of the proposed algorithms through statistical analysis
and empirical experiments using both synthetic and real data sets.
Wan D. Bae is currently an assistant professor in the Mathematics, Statistics and Computer Science Department at the University of Wisconsin-Stout. She received her Ph.D. in Computer Science from the University of Denver in 2007. Dr. Bae’s current research interests include online query processing, Geographic Information Systems, digital mapping, multidimensional data analysis and data mining in spatial and spatiotemporal databases. Shayma Alkobaisi is currently an assistant professor at the College of Information Technology in the United Arab Emirates University. She received her Ph.D. in Computer Science from the University of Denver in 2008. Dr. Alkobaisi’s research interests include uncertainty management in spatiotemporal databases, online query processing in spatial databases, Geographic Information Systems and computational geometry. Seon Ho Kim is currently an associate professor in the Computer Science & Information Technology Department at the University of District of Columbia. He received his Ph.D. in Computer Science from the University of Southern California in 1999. Dr. Kim’s primary research interests include design and implementation of multimedia storage systems, and databases, spatiotemporal databases, and GIS. He co-chaired the 2004 ACM Workshop on Next Generation Residential Broadband Challenges in conjunction with the ACM Multimedia Conference. Sada Narayanappa is currently an advanced computing technologist at Jeppesen. He received his Ph.D. in Mathematics and Computer Science from the University of Denver in 2006. Dr. Narayanappa’s primary research interests include computational geometry, graph theory, algorithms, design and implementation of databases. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his Ph.D. degree in Computer Science from the University of Southern California in August 1996. Dr. Shahabi’s current research interests include Peer-to-Peer Systems, Streaming Architectures, Geospatial Data Integration and Multidimensional Data Analysis. He is currently on the editorial board of ACM Computers in Entertainment magazine. He is also serving on many conference program committees such as ICDE, SSTD, ACM SIGMOD, ACM GIS. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations. 相似文献
Cyrus ShahabiEmail: |
Wan D. Bae is currently an assistant professor in the Mathematics, Statistics and Computer Science Department at the University of Wisconsin-Stout. She received her Ph.D. in Computer Science from the University of Denver in 2007. Dr. Bae’s current research interests include online query processing, Geographic Information Systems, digital mapping, multidimensional data analysis and data mining in spatial and spatiotemporal databases. Shayma Alkobaisi is currently an assistant professor at the College of Information Technology in the United Arab Emirates University. She received her Ph.D. in Computer Science from the University of Denver in 2008. Dr. Alkobaisi’s research interests include uncertainty management in spatiotemporal databases, online query processing in spatial databases, Geographic Information Systems and computational geometry. Seon Ho Kim is currently an associate professor in the Computer Science & Information Technology Department at the University of District of Columbia. He received his Ph.D. in Computer Science from the University of Southern California in 1999. Dr. Kim’s primary research interests include design and implementation of multimedia storage systems, and databases, spatiotemporal databases, and GIS. He co-chaired the 2004 ACM Workshop on Next Generation Residential Broadband Challenges in conjunction with the ACM Multimedia Conference. Sada Narayanappa is currently an advanced computing technologist at Jeppesen. He received his Ph.D. in Mathematics and Computer Science from the University of Denver in 2006. Dr. Narayanappa’s primary research interests include computational geometry, graph theory, algorithms, design and implementation of databases. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his Ph.D. degree in Computer Science from the University of Southern California in August 1996. Dr. Shahabi’s current research interests include Peer-to-Peer Systems, Streaming Architectures, Geospatial Data Integration and Multidimensional Data Analysis. He is currently on the editorial board of ACM Computers in Entertainment magazine. He is also serving on many conference program committees such as ICDE, SSTD, ACM SIGMOD, ACM GIS. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations. 相似文献
2.
Retrieval of Spatial Join Pattern Instances from Sensor Networks 总被引:1,自引:1,他引:0
We study the continuous evaluation of spatial join queries and extensions thereof, defined by interesting combinations of
sensor readings (events) that co-occur in a spatial neighborhood. An example of such a pattern is “a high temperature reading
in the vicinity of at least four high-pressure readings”. We devise protocols for ‘in-network’ evaluation of this class of
queries, aiming at the minimization of power consumption. In addition, we develop cost models that suggest the appropriateness
of each protocol, based on various factors, including selectivity of query elements, energy requirements for sensing, and
network topology. Finally, we experimentally compare the effectiveness of the proposed solutions on an experimental platform
that emulates real sensor networks.
Man Lung Yiu received the Bachelor Degree in Computer Engineering and the Ph.D. Degree in Computer Science from the University of Hong Kong in 2002 and 2006 respectively. He is currently an assistant professor at Department of Computer Science, Aalborg University. His research interests include databases and data mining, especially advanced query processing and mining techniques for complex types of data. Nikos Mamoulis received the diploma in Computer Engineering and Informatics in 1995 from the University of Patras, Greece, and the Ph.D. degree in computer science in 2000 from the Hong Kong University of Science and Technology. Since September 2001, he has been a faculty member of the Department of Computer Science at the University of Hong Kong, currently an associate professor. In the past, he has worked as a postdoctoral researcher at the Centrum voor Wiskunde en Informatica (CWI), The Netherlands. His research interests include complex data management, data mining, advanced indexing and query processing, and constraint satisfaction problems. He has published more than 75 articles in reputable international conferences and journals and served in the program committees of numerous database and data mining conferences. Spiridon Bakiras received his B.S. degree (1993) in Electrical and Computer Engineering from the National Technical University of Athens, his MS degree (1994) in Telematics from the University of Surrey, and his Ph.D. degree (2000) in Electrical Engineering from the University of Southern California. Currently, he is an Assistant Professor in the Department of Mathematics and Computer Science at John Jay College, CUNY. Before that, he held teaching and research positions at the University of Hong Kong and the Hong Kong University of Science and Technology. His research interests include high-speed networks, peer-to-peer systems, mobile computing, and spatial databases. He is a member of the ACM and the IEEE. 相似文献
Spiridon BakirasEmail: |
Man Lung Yiu received the Bachelor Degree in Computer Engineering and the Ph.D. Degree in Computer Science from the University of Hong Kong in 2002 and 2006 respectively. He is currently an assistant professor at Department of Computer Science, Aalborg University. His research interests include databases and data mining, especially advanced query processing and mining techniques for complex types of data. Nikos Mamoulis received the diploma in Computer Engineering and Informatics in 1995 from the University of Patras, Greece, and the Ph.D. degree in computer science in 2000 from the Hong Kong University of Science and Technology. Since September 2001, he has been a faculty member of the Department of Computer Science at the University of Hong Kong, currently an associate professor. In the past, he has worked as a postdoctoral researcher at the Centrum voor Wiskunde en Informatica (CWI), The Netherlands. His research interests include complex data management, data mining, advanced indexing and query processing, and constraint satisfaction problems. He has published more than 75 articles in reputable international conferences and journals and served in the program committees of numerous database and data mining conferences. Spiridon Bakiras received his B.S. degree (1993) in Electrical and Computer Engineering from the National Technical University of Athens, his MS degree (1994) in Telematics from the University of Surrey, and his Ph.D. degree (2000) in Electrical Engineering from the University of Southern California. Currently, he is an Assistant Professor in the Department of Mathematics and Computer Science at John Jay College, CUNY. Before that, he held teaching and research positions at the University of Hong Kong and the Hong Kong University of Science and Technology. His research interests include high-speed networks, peer-to-peer systems, mobile computing, and spatial databases. He is a member of the ACM and the IEEE. 相似文献
3.
Shape deformation in continuous map generalization 总被引:2,自引:0,他引:2
Jeff Danciger Satyan L. Devadoss John Mugno Don Sheehy Rachel Ward 《GeoInformatica》2009,13(2):203-221
Given a collection of regions on a map, we seek a method of continuously altering the regions as the scale is varied. This
is formalized and brought to rigor as well-defined problems in homotopic deformation. We ask the regions to preserve topology,
area-ratios, and relative position as they change over time. A solution is presented using differential methods and computational
geometric techniques. Most notably, an application of this method is used to provide an algorithm to obtain cartograms.
Jeff Danciger Jeffrey received his undergraduate degree from the College of Creative Studies at UCSB in mathematics and physics. He is currently working on his Ph.D. in mathematics at Stanford University. His research interests include low dimensional topology and geometric analysis. Satyan L. Devadoss is an Associate Professor of Mathematics at Williams College. His research interests lie in the interplay between topology and geometry, notably in applications to theoretical physics (moduli spaces and string theory) and computer science (cartography and polytopes). John Mugno received his undergraduate degree from Williams College and is currently continuing his studies in mathematics at the University of Maryland. His areas of interest include combinatorics and topology. Don Sheehy received his undergraduate degree in Princeton University and is currently pursuing a PhD in Computer Science at Carnegie Mellon University. His research focuses on computational geometry algorithms for meshing. Rachel Ward received her undergraduate degree at the University of Texas at Austin. She is now a PhD student at Princeton University in the Program in Applied and Computational Mathematics. Her current work is in the area of compressed sensing, combining tools from computational harmonic analysis, probability, and optimization theory. 相似文献
Rachel WardEmail: |
Jeff Danciger Jeffrey received his undergraduate degree from the College of Creative Studies at UCSB in mathematics and physics. He is currently working on his Ph.D. in mathematics at Stanford University. His research interests include low dimensional topology and geometric analysis. Satyan L. Devadoss is an Associate Professor of Mathematics at Williams College. His research interests lie in the interplay between topology and geometry, notably in applications to theoretical physics (moduli spaces and string theory) and computer science (cartography and polytopes). John Mugno received his undergraduate degree from Williams College and is currently continuing his studies in mathematics at the University of Maryland. His areas of interest include combinatorics and topology. Don Sheehy received his undergraduate degree in Princeton University and is currently pursuing a PhD in Computer Science at Carnegie Mellon University. His research focuses on computational geometry algorithms for meshing. Rachel Ward received her undergraduate degree at the University of Texas at Austin. She is now a PhD student at Princeton University in the Program in Applied and Computational Mathematics. Her current work is in the area of compressed sensing, combining tools from computational harmonic analysis, probability, and optimization theory. 相似文献
4.
Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories
of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved.
In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition
of the pattern ‘one object is leading others’, which is based on behavioural patterns discussed in the behavioural ecology
literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum
number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis
for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection,
given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms
efficiently report leadership patterns.
Mattias Andersson received his M.Sc. in Computer Science at Lund university, Sweden. Currently he is completing his Ph.D. thesis at the same university. He works in computational geometry, specialising in geometric networks. Applications of this work include transportation networks, computer graphics and geographic information systems (GIS). Joachim Gudmundsson received his Ph.D. in computer science from Lund University in Sweden. During 2001-2004 he was a postdoctoral researcher at Utrecht University and at the Technical University of Eindhoven in the Netherlands. Since 2005 he has worked as a senior researcher at NICTA in Sydney, where he is currently heading the DMiST project (Data Mining in Spatio-Temporal sets). His research interests are computational geometry and approximation algorithms. Patrick Laube holds an M.Sc. (Geography, 1999) and a Ph.D. degree (Sciences, 2005) from University of Zurich, Switzerland. His thesis covered the analysis of movement data, presenting an approach for spatio-temporal data mining based on pattern detection and visualisation. Recently he was a research fellow at the Spatial Analysis Facility at the University of Auckland, NZ, and a visiting scholar at the GeoVISTA Center at Penn State University, PA, USA. He is currently working as a research fellow in the Department of Geomatics at the University of Melbourne, Australia, focussing on distributed spatial computing and geosensor networks. Thomas Wolle studied computer science at Friedrich-Schiller-University Jena, Germany, where he graduated in 2001. In the same year, he started as a research student at Utrecht University, the Netherlands, where he obtained his Ph.D. degree in 2005. His research focussed on graph algorithms, more specifically on graphs of bounded treewidth. In 2006, he joined the DMiST project as a researcher at NICTA in Sydney, where he works on algorithms for geometric problems that emerge in the field of spatio-temporal data mining. 相似文献
Thomas Wolle (Corresponding author)Email: |
Mattias Andersson received his M.Sc. in Computer Science at Lund university, Sweden. Currently he is completing his Ph.D. thesis at the same university. He works in computational geometry, specialising in geometric networks. Applications of this work include transportation networks, computer graphics and geographic information systems (GIS). Joachim Gudmundsson received his Ph.D. in computer science from Lund University in Sweden. During 2001-2004 he was a postdoctoral researcher at Utrecht University and at the Technical University of Eindhoven in the Netherlands. Since 2005 he has worked as a senior researcher at NICTA in Sydney, where he is currently heading the DMiST project (Data Mining in Spatio-Temporal sets). His research interests are computational geometry and approximation algorithms. Patrick Laube holds an M.Sc. (Geography, 1999) and a Ph.D. degree (Sciences, 2005) from University of Zurich, Switzerland. His thesis covered the analysis of movement data, presenting an approach for spatio-temporal data mining based on pattern detection and visualisation. Recently he was a research fellow at the Spatial Analysis Facility at the University of Auckland, NZ, and a visiting scholar at the GeoVISTA Center at Penn State University, PA, USA. He is currently working as a research fellow in the Department of Geomatics at the University of Melbourne, Australia, focussing on distributed spatial computing and geosensor networks. Thomas Wolle studied computer science at Friedrich-Schiller-University Jena, Germany, where he graduated in 2001. In the same year, he started as a research student at Utrecht University, the Netherlands, where he obtained his Ph.D. degree in 2005. His research focussed on graph algorithms, more specifically on graphs of bounded treewidth. In 2006, he joined the DMiST project as a researcher at NICTA in Sydney, where he works on algorithms for geometric problems that emerge in the field of spatio-temporal data mining. 相似文献
5.
We address the problem of optimizing the maintenance of continuous queries in Moving Objects Databases, when a set of pending
continuous queries need to be reevaluated as a result of bulk updates to the trajectories of moving objects. Such bulk updates
may happen when traffic abnormalities, e.g., accidents or road works, affect a subset of trajectories in the corresponding
regions, throughout the duration of these abnormalities. The updates to the trajectories may in turn affect the correctness
of the answer sets for the pending continuous queries in much larger geographic areas. We present a comprehensive set of techniques,
both static and dynamic, for improving the performance of reevaluating the continuous queries in response to the bulk updates.
The static techniques correspond to specifying the values for the various semantic dimensions of trigger execution. The dynamic
techniques include an in-memory shared reevaluation algorithm, extending query indexing to queries described by trajectories
and query reevaluation ordering based on space-filling curves. We have completely implemented our system prototype on top
of an existing Object-Relational Database Management System, Oracle 9i, and conducted extensive experimental evaluations using
realistic data sets to demonstrate the validity of our approach.
Hui Ding received the B.E. degree in electronic engineering from Tsinghua University, Beijing, China in 2003. He is now a Ph.D. student in the deparment of electrical engineering and computer science at Northwestern University, U.S.A. His research interest is in spatio-temporal databases and data management in mobile computing. Goce Trajcevski is a researcher at the Dept. of Electrical Engineering and Computer Science at the Northwestern University. His main interests are in the areas of mobile data management and sensor networks. He received a BS from the University of Sts. Kiril & Metodi, and the MS and PhD from the University of Illinois at Chicago. He coauthored over 25 publications, participated as a PC member of several conferences and workshops, and was ACM DiSC associate editor 2003–2005. He is a member of IEEE and ACM. Peter Scheuermann is a Professor of Electrical Engineering and Computer Science at Northwestern University. He has held visiting professor positions with the Free University of Amsterdam, the University of Hamburg and the Swiss Federal Institute of Technology, Zurich. During 1997–1998 he served as Program Director for Operating Systems at the NSF. Dr. Scheuermann has served on the editorial board of the Communications of ACM, The VLB Journal and IEEE Transactions on Knowledge and Data Engineering. His current research interests are in parallel and distributed database systems, mobile computing, spatial databases and data mining. He has published more than 100 journal and conference papers. Peter Scheuermann is a Fellow of IEEE. 相似文献
Peter ScheuermannEmail: |
Hui Ding received the B.E. degree in electronic engineering from Tsinghua University, Beijing, China in 2003. He is now a Ph.D. student in the deparment of electrical engineering and computer science at Northwestern University, U.S.A. His research interest is in spatio-temporal databases and data management in mobile computing. Goce Trajcevski is a researcher at the Dept. of Electrical Engineering and Computer Science at the Northwestern University. His main interests are in the areas of mobile data management and sensor networks. He received a BS from the University of Sts. Kiril & Metodi, and the MS and PhD from the University of Illinois at Chicago. He coauthored over 25 publications, participated as a PC member of several conferences and workshops, and was ACM DiSC associate editor 2003–2005. He is a member of IEEE and ACM. Peter Scheuermann is a Professor of Electrical Engineering and Computer Science at Northwestern University. He has held visiting professor positions with the Free University of Amsterdam, the University of Hamburg and the Swiss Federal Institute of Technology, Zurich. During 1997–1998 he served as Program Director for Operating Systems at the NSF. Dr. Scheuermann has served on the editorial board of the Communications of ACM, The VLB Journal and IEEE Transactions on Knowledge and Data Engineering. His current research interests are in parallel and distributed database systems, mobile computing, spatial databases and data mining. He has published more than 100 journal and conference papers. Peter Scheuermann is a Fellow of IEEE. 相似文献
6.
An important privacy issue in Location Based Services is to hide a user’s identity while still provide quality location based
services. Previous work has addressed the problem of locational -anonymity either based on centralized or decentralized schemes. However, a centralized scheme relies on an anonymizing server
(AS) for location cloaking, which may become the performance bottleneck when there are large number of clients. More importantly,
holding information in a centralized place is more vulnerable to malicious attacks. A decentralized scheme depends on peer
communication to cloak locations and is more scalable. However, it may pose too much computation and communication overhead
to the clients. The service fulfillment rate may also be unsatisfied especially when there are not enough peers nearby. This
paper proposes a new hybrid framework called HiSC that balances the load between the AS and mobile clients. HiSC partitions
the space into base cells and a mobile client claims a surrounding area consisting of base cells. The number of mobile clients
in the surrounding cells is kept and updated at both client and AS sides. A mobile client can either request cloaking service
from the centralized AS or use a peer-to-peer approach for spatial cloaking based on personalized privacy, response time,
and service quality requirements. HiSC can elegantly distribute the work load between the AS and the mobile clients by tuning
one system parameter base cell size and two client parameters - surrounding cell size and tolerance count. By integrating salient features of two schemes, HiSC successfully preserves query anonymity and provides more scalable and
consistent service. Both the AS and the clients can enjoy much less work load. Additionally, we propose a simple yet effective
random range shifting algorithm to prevent possible privacy leakage that would exist in the original P2P approach. Our experiments
show that HiSC can elegantly balance the work load based on privacy requirements and client distribution. HiSC provides close
to optimal service quality. Meanwhile, it reduces the response time by more than an order of magnitude from both the P2P scheme
and the centralized scheme when anonymity level(value of ) or number of clients is large. It also reduces the update message cost of the AS by nearly 6 times and the peer searching
message cost of the clients by more than an order of magnitude.
Chengyang Zhang received his B.S. degree in Industrial Automation from University of Science and Technology, Beijing in 2000 and master degree in computer system engineering from University of Science and Technology, Beijing in 2003. He is currently a Ph.D. student at the Computer Science and Engineering department of University of North Texas, Denton, TX, USA. His research interests include location based services, spatio-temporal databases, and geo-stream data management systems. Yan Huang received her B.S. degree in Computer Science from Beijing University, Beijing, China, in July 1997 and Ph.D. degree in Computer Science from University of Minnesota, Twin-cities, MN, USA, in July 2003. She is currently an assistant professor at the Computer Science and Engineering Department of University of North Texas, Denton, TX, USA. Her research interests include geo-sensor networks, spatial databases, and data mining. She is a member of the IEEE Computer Society, the ACM, and the ACM SIGMOD. Her research is supported by Texas Advanced Research Program (ARP), Oak Ridge National Lab, and NSF. 相似文献
Chengyang ZhangEmail: |
Chengyang Zhang received his B.S. degree in Industrial Automation from University of Science and Technology, Beijing in 2000 and master degree in computer system engineering from University of Science and Technology, Beijing in 2003. He is currently a Ph.D. student at the Computer Science and Engineering department of University of North Texas, Denton, TX, USA. His research interests include location based services, spatio-temporal databases, and geo-stream data management systems. Yan Huang received her B.S. degree in Computer Science from Beijing University, Beijing, China, in July 1997 and Ph.D. degree in Computer Science from University of Minnesota, Twin-cities, MN, USA, in July 2003. She is currently an assistant professor at the Computer Science and Engineering Department of University of North Texas, Denton, TX, USA. Her research interests include geo-sensor networks, spatial databases, and data mining. She is a member of the IEEE Computer Society, the ACM, and the ACM SIGMOD. Her research is supported by Texas Advanced Research Program (ARP), Oak Ridge National Lab, and NSF. 相似文献
7.
Calculating operators of continuously moving objects presents some unique challenges, especially when the operators involve
aggregation or the concept of congestion, which happens when the number of moving objects in a changing or dynamic query space
exceeds some threshold value. This paper presents the following six d-dimensional moving object operators: (1) MaxCount (or MinCount), which finds the Maximum (or Minimum) number of moving objects simultaneously present in the dynamic query space at any
time during the query time interval. (2) CountRange, which finds a count of point objects whose trajectories intersect the dynamic query space during the query time interval.
(3) ThresholdRange, which finds the set of time intervals during which the dynamic query space is congested. (4) ThresholdSum, which finds the total length of all the time intervals during which the dynamic query space is congested. (5) ThresholdCount, which finds the number of disjoint time intervals during which the dynamic query space is congested. And (6) ThresholdAverage, which finds the average length of time of all the time intervals when the dynamic query space is congested. For these operators
separate algorithms are given to find only estimate or only precise values. Experimental results from more than 7,500 queries
indicate that the estimation algorithms produce fast, efficient results with error under 5%.
Scot Anderson obtained his Ph.D. degree in Computer Science from the University of Nebraska—Lincoln in 2007. He is currently an assistant professor at Southern Adventist University. His research interests are geographic information systems, moving objects, and spatio-temporal data. Peter Revesz holds a Ph.D. degree in Computer Science from Brown University and was a postdoctoral fellow at the University of Toronto before joining the University of Nebraska—Lincoln, where he is currently a full professor in the Department of Computer Science and Engineering. He is well-known as a co-inventor of constraint databases in a highly-cited joint paper with Paris Kanellakis and Gabriel Kuper. He is the author of the book “Introduction to Constraint Databases”, which was published by Springer in 2002. His current research interests include geographic information systems and spatio-temporal databases. He has been a visiting professor at the University of Athens in Greece, the University of Hasselt in Belgium and the Max Planck Institute for Computer Science and the University of Freiburg in Germany. He was awarded a Fulbright Award and an Alexander von Humboldt Research Fellowship. 相似文献
Peter Revesz (Corresponding author)Email: |
Scot Anderson obtained his Ph.D. degree in Computer Science from the University of Nebraska—Lincoln in 2007. He is currently an assistant professor at Southern Adventist University. His research interests are geographic information systems, moving objects, and spatio-temporal data. Peter Revesz holds a Ph.D. degree in Computer Science from Brown University and was a postdoctoral fellow at the University of Toronto before joining the University of Nebraska—Lincoln, where he is currently a full professor in the Department of Computer Science and Engineering. He is well-known as a co-inventor of constraint databases in a highly-cited joint paper with Paris Kanellakis and Gabriel Kuper. He is the author of the book “Introduction to Constraint Databases”, which was published by Springer in 2002. His current research interests include geographic information systems and spatio-temporal databases. He has been a visiting professor at the University of Athens in Greece, the University of Hasselt in Belgium and the Max Planck Institute for Computer Science and the University of Freiburg in Germany. He was awarded a Fulbright Award and an Alexander von Humboldt Research Fellowship. 相似文献
8.
The Optimal Sequenced Route (OSR) query strives to find a route of minimum length starting from a given source location and passing through a number of typed locations in a specific sequence imposed on the types of the locations. In this paper, we propose a pre-computation approach
to OSR query in both vector and metric spaces. We exploit the geometric properties of the solution space and theoretically
prove its relation to additively weighted Voronoi diagrams. Our approach recursively accesses these diagrams to incrementally build the OSR. Introducing the analogous diagrams for
the space of road networks, we show that our approach is also efficiently applicable to this metric space. Our experimental
results verify that our pre-computation approach outperforms the previous index-based approaches in terms of query response
time.
This research has been funded in part by NSF grants EEC-9529152 (IMSC ERC), IIS-0238560 (PECASE), IIS-0324955 (ITR), IIS-0534761,
and unrestricted cash gifts from Google and Microsoft. Any opinions, findings, and conclusions or recommendations expressed
in this material are those of the author(s) and do not necessarily reflect the views of the NSF.
Mehdi Sharifzadeh received his B.S. and M.S. degrees in Computer Engineering from Sharif University of Technology in Tehran, Iran, in 1995, and 1998, respectively. He received his Ph.D. degree in Computer Science from the University of Southern California in May 2007. His research interests include spatial and spatio-temporal databases, data stream processing, and sensor networks. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center at the University of Southern California. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. degrees in Computer Science from the University of Southern California in May 1993 and August 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems and on the editorial board of ACM Computers in Entertainment magazine. He is also a member of the steering committees of IEEE NetDB and general co-chair of ACM GIS 2007. He serves on many conference program committees such as ACM SIGKDD 2006-08, IEEE ICDE 2006 and 08, SSTD 2005-08 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 NSF CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers. In 2001, he also received an award from the Okawa Foundations. 相似文献
Mehdi Sharifzadeh (Corresponding author)Email: URL: http://infolab.usc.edu |
Cyrus ShahabiEmail: |
Mehdi Sharifzadeh received his B.S. and M.S. degrees in Computer Engineering from Sharif University of Technology in Tehran, Iran, in 1995, and 1998, respectively. He received his Ph.D. degree in Computer Science from the University of Southern California in May 2007. His research interests include spatial and spatio-temporal databases, data stream processing, and sensor networks. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center at the University of Southern California. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. degrees in Computer Science from the University of Southern California in May 1993 and August 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems and on the editorial board of ACM Computers in Entertainment magazine. He is also a member of the steering committees of IEEE NetDB and general co-chair of ACM GIS 2007. He serves on many conference program committees such as ACM SIGKDD 2006-08, IEEE ICDE 2006 and 08, SSTD 2005-08 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 NSF CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers. In 2001, he also received an award from the Okawa Foundations. 相似文献
9.
Advances in GML for Geospatial Applications 总被引:1,自引:0,他引:1
Chang-Tien Lu Raimundo F. Dos SantosJr Lakshmi N. Sripada Yufeng Kou 《GeoInformatica》2007,11(1):131-157
This paper presents a study of Geography Markup Language (GML), the issues that arise from using GML for spatial applications,
including storage, parsing, querying and visualization, as well as the use of GML for mobile devices and web services. GML
is a modeling language developed by the Open Geospatial Consortium (OGC) as a medium of uniform geographic data storage and
exchange among diverse applications. Many new XML-based languages are being developed as open standards in various areas of
application. It would be beneficial to integrate such languages with GML during the developmental stages, taking full advantage
of a non-proprietary universal standard. As GML is a relatively new language still in development, data processing techniques
need to be refined further in order for GML to become a more efficient medium for geospatial applications.
Chang-Tien(C.T.) Lu received the BS degree in Computer Science and Engineering from the Tatung Institute of Technology, Taipei, Taiwan, in 1991, the MS degree in Computer Science from the Georgia Institute of Technology, Atlanta, GA, in 1996, and the Ph.D. degree in Computer Science from the University of Minnesota, Minneapolis, MN, in 2001. He is currently an assistant professor in the Department of Computer Science at Virginia Polytechnic Institute and State University, and is the founding director of the Spatial Data Management Laboratory. His research interests include spatial database, data mining, data warehousing, geographic information systems, and intelligent transportation systems. Dr. Lu is also affiliated with Virginia Tech Civil and Environmental Engineering Department, Center for Geospatial Information Technology, and Virginia Tech Transportation Institute. Raimundo Dos Santos received a Bachelor’s Degree in Computer Science from the University of South Florida. He is currently a PhD. candidate in the Department of Computer Science at Virginia Polytechnic Institute and State University. His research focuses on Spatial Data Management, including retrieval, exchange, and processing of information for Geographic Information Systems and Location-Based Services. Other interests include Geography Markup Language (GML), and data visualization. Lakshmi N Sripada received an MS in Information Systems from Virginia Polytechnic and State University in 2004. Her research interests include Data Visualization, GML, and Geographic Information Systems. Yufeng Kou received a BS degree in Computer Science from Northwestern Polytechnic University, XiAn, China, in 1996, a MS degree in Computer Science from Beijing University of Post and Telecommunications in 1999. He is a PhD candidate in Computer Science Department, Virginia Polytechnic Institute and State University. His research interests include spatial data analysis, data mining, data warehousing, and Geographic Information Systems. 相似文献
Yufeng KouEmail: |
Chang-Tien(C.T.) Lu received the BS degree in Computer Science and Engineering from the Tatung Institute of Technology, Taipei, Taiwan, in 1991, the MS degree in Computer Science from the Georgia Institute of Technology, Atlanta, GA, in 1996, and the Ph.D. degree in Computer Science from the University of Minnesota, Minneapolis, MN, in 2001. He is currently an assistant professor in the Department of Computer Science at Virginia Polytechnic Institute and State University, and is the founding director of the Spatial Data Management Laboratory. His research interests include spatial database, data mining, data warehousing, geographic information systems, and intelligent transportation systems. Dr. Lu is also affiliated with Virginia Tech Civil and Environmental Engineering Department, Center for Geospatial Information Technology, and Virginia Tech Transportation Institute. Raimundo Dos Santos received a Bachelor’s Degree in Computer Science from the University of South Florida. He is currently a PhD. candidate in the Department of Computer Science at Virginia Polytechnic Institute and State University. His research focuses on Spatial Data Management, including retrieval, exchange, and processing of information for Geographic Information Systems and Location-Based Services. Other interests include Geography Markup Language (GML), and data visualization. Lakshmi N Sripada received an MS in Information Systems from Virginia Polytechnic and State University in 2004. Her research interests include Data Visualization, GML, and Geographic Information Systems. Yufeng Kou received a BS degree in Computer Science from Northwestern Polytechnic University, XiAn, China, in 1996, a MS degree in Computer Science from Beijing University of Post and Telecommunications in 1999. He is a PhD candidate in Computer Science Department, Virginia Polytechnic Institute and State University. His research interests include spatial data analysis, data mining, data warehousing, and Geographic Information Systems. 相似文献
10.
The Effects of Navigation Sensors and Spatial Road Network Data Quality on the Performance of Map Matching Algorithms 总被引:1,自引:0,他引:1
Map matching algorithms are utilised to support the navigation module of advanced transport telematics systems. The objective
of this paper is to develop a framework to quantify the effects of spatial road network data and navigation sensor data on
the performance of map matching algorithms. Three map matching algorithms are tested with different spatial road network data
(map scale 1:1,250; 1:2,500 and 1:50,000) and navigation sensor data (global positioning system (GPS) and GPS augmented with
deduced reckoning) in order to quantify their performance. The algorithms are applied to different road networks of varying
complexity. The performance of the algorithms is then assessed for a suburban road network using high precision positioning
data obtained from GPS carrier phase observables. The results show that there are considerable effects of spatial road network
data on the performance of map matching algorithms. For an urban road network, the results suggest that both the quality of
spatial road network data and the type of navigation system affect the link identification performance of map matching algorithms.
Dr. Mohammed Quddus obtained a PhD from Imperial College London in 2005 where he was working as a research assistant for four years and a research fellow for one year on a number of research projects. He received an MEng degree in Civil Engineering from the National University of Singapore in 2001 and a BSc in Civil Engineering from BUET (Bangladesh University of Engineering and Technology) in 1998. He joined Loughborough University as a lecturer in transport studies in 2006.
Dr. Robert Noland is Reader in Transport and Environmental Policy and heads the Environment and Policy Research Group within the Centre for Transport Studies. He received his PhD at the University of Pennsylvania in Energy Management and Environmental Policy. Prior to joining Imperial College he was a Policy Analyst at the US Environmental Protection Agency and also conducted post-doctoral research in the Economics Department at the University of California at Irvine.
Prof Washington Ochieng is Professor of Positioning and Navigation Systems at the Centre for Transport Studies (CTS) in the Department of Civil and Environmental Engineering at Imperial College London. He is also the Director of the Departmental MSc Programmes and the Imperial College Engineering Geomatics Group (ICEGG). Dr. Ochieng is a Fellow of the Royal Institute of Navigation (FRIN) and the Institution of Civil Engineering Surveyors (FInstCES). He is a Member of Council and Trustee of the Royal Institute of Navigation, Member of the Institution of Civil Engineers (MICE), the Institution of Highways and Transportation (MIHT), and the United States Institute of Navigation.
相似文献
Robert B. NolandEmail: |
Dr. Mohammed Quddus obtained a PhD from Imperial College London in 2005 where he was working as a research assistant for four years and a research fellow for one year on a number of research projects. He received an MEng degree in Civil Engineering from the National University of Singapore in 2001 and a BSc in Civil Engineering from BUET (Bangladesh University of Engineering and Technology) in 1998. He joined Loughborough University as a lecturer in transport studies in 2006.
Dr. Robert Noland is Reader in Transport and Environmental Policy and heads the Environment and Policy Research Group within the Centre for Transport Studies. He received his PhD at the University of Pennsylvania in Energy Management and Environmental Policy. Prior to joining Imperial College he was a Policy Analyst at the US Environmental Protection Agency and also conducted post-doctoral research in the Economics Department at the University of California at Irvine.
Prof Washington Ochieng is Professor of Positioning and Navigation Systems at the Centre for Transport Studies (CTS) in the Department of Civil and Environmental Engineering at Imperial College London. He is also the Director of the Departmental MSc Programmes and the Imperial College Engineering Geomatics Group (ICEGG). Dr. Ochieng is a Fellow of the Royal Institute of Navigation (FRIN) and the Institution of Civil Engineering Surveyors (FInstCES). He is a Member of Council and Trustee of the Royal Institute of Navigation, Member of the Institution of Civil Engineers (MICE), the Institution of Highways and Transportation (MIHT), and the United States Institute of Navigation.
相似文献
11.
In this paper, a statistical model called statistical local spatial relations (SLSR) is presented as a novel technique of
a learning model with spatial and statistical information for semantic image classification. The model is inspired by probabilistic
Latent Semantic Analysis (PLSA) for text mining. In text analysis, PLSA is used to discover topics in a corpus using the bag-of-word
document representation. In SLSR, we treat image categories as topics, therefore an image containing instances of multiple
categories can be modeled as a mixture of topics. More significantly, SLSR introduces spatial relation information as a factor
which is not present in PLSA. SLSR has rotation, scale, translation and affine invariant properties and can solve partial
occlusion problems. Using the Dirichlet process and variational Expectation-Maximization learning algorithm, SLSR is developed
as an implementation of an image classification algorithm. SLSR uses an unsupervised process which can capture both spatial
relations and statistical information simultaneously. The experiments are demonstrated on some standard data sets and show
that the SLSR model is a promising model for semantic image classification problems.
Dongfeng Han received the B.Sc. 2002 and M.S. 2005 in computer science and technology from Jilin University, Changchun, P. R. China. From 2005, he pursuits the PhD degree in computer science and technology Jilin University. His research interests include computer vision, image processing, machine learning and pattern recognition. Wenhui Li received the PhD degree in computer science from Jilin University in 1996. Now he is a professor of Jilin University. His research interests include computer vision, computer graphic and virtual reality. Zongcheng Li undergraduated student of Shandong University of Technology, P. R. China. His research interests include computer vision and image processing. 相似文献
Wenhui Li (Corresponding author)Email: |
Dongfeng Han received the B.Sc. 2002 and M.S. 2005 in computer science and technology from Jilin University, Changchun, P. R. China. From 2005, he pursuits the PhD degree in computer science and technology Jilin University. His research interests include computer vision, image processing, machine learning and pattern recognition. Wenhui Li received the PhD degree in computer science from Jilin University in 1996. Now he is a professor of Jilin University. His research interests include computer vision, computer graphic and virtual reality. Zongcheng Li undergraduated student of Shandong University of Technology, P. R. China. His research interests include computer vision and image processing. 相似文献
12.
Similarity searching in metric spaces has a vast number of applications in several fields like multimedia databases, text
retrieval, computational biology, and pattern recognition. In this context, one of the most important similarity queries is
the k nearest neighbor (k-NN) search. The standard best-first k-NN algorithm uses a lower bound on the distance to prune objects during the search. Although optimal in several aspects,
the disadvantage of this method is that its space requirements for the priority queue that stores unprocessed clusters can
be linear in the database size. Most of the optimizations used in spatial access methods (for example, pruning using MinMaxDist)
cannot be applied in metric spaces, due to the lack of geometric properties. We propose a new k-NN algorithm that uses distance estimators, aiming to reduce the storage requirements of the search algorithm. The method stays optimal, yet it can significantly prune
the priority queue without altering the output of the query. Experimental results with synthetic and real datasets confirm
the reduction in storage space of our proposed algorithm, showing savings of up to 80% of the original space requirement.
Benjamin Bustos is an assistant professor in the Department of Computer Science at the University of Chile. He is also a researcher at the Millennium Nucleus Center for Web Research. His research interests are similarity searching and multimedia information retrieval. He has a doctoral degree in natural sciences from the University of Konstanz, Germany. Contact him at bebustos@dcc.uchile.cl. Gonzalo Navarro earned his PhD in Computer Science at the University of Chile in 1998, where he is now Full Professor. His research interests include similarity searching, text databases, compression, and algorithms and data structures in general. He has coauthored a book on string matching and around 200 international papers. He has (co)chaired international conferences SPIRE 2001, SCCC 2004, SPIRE 2005, SIGIR Posters 2005, IFIP TCS 2006, and ENC 2007 Scalable Pattern Recognition track; and belongs to the Editorial Board of Information Retrieval Journal. He is currently Head of the Department of Computer Science at University of Chile, and Head of the Millenium Nucleus Center for Web Research, the largest Chilean project in Computer Science research. 相似文献
Gonzalo NavarroEmail: |
Benjamin Bustos is an assistant professor in the Department of Computer Science at the University of Chile. He is also a researcher at the Millennium Nucleus Center for Web Research. His research interests are similarity searching and multimedia information retrieval. He has a doctoral degree in natural sciences from the University of Konstanz, Germany. Contact him at bebustos@dcc.uchile.cl. Gonzalo Navarro earned his PhD in Computer Science at the University of Chile in 1998, where he is now Full Professor. His research interests include similarity searching, text databases, compression, and algorithms and data structures in general. He has coauthored a book on string matching and around 200 international papers. He has (co)chaired international conferences SPIRE 2001, SCCC 2004, SPIRE 2005, SIGIR Posters 2005, IFIP TCS 2006, and ENC 2007 Scalable Pattern Recognition track; and belongs to the Editorial Board of Information Retrieval Journal. He is currently Head of the Department of Computer Science at University of Chile, and Head of the Millenium Nucleus Center for Web Research, the largest Chilean project in Computer Science research. 相似文献
13.
Multi-level Topological Relations Between Spatial Regions Based Upon Topological Invariants 总被引:1,自引:0,他引:1
Topological relations have played important roles in spatial query, analysis and reasoning. In a two-dimensional space (IR2), most existing topological models can distinguish the eight basic topological relations between two spatial regions. Due
to the arbitrariness and complexity of topological relations between spatial regions, it is difficult for these models to
describe the order property of transformations among the topological relations, which is important for detailed analysis of
spatial relations. In order to overcome the insufficiency in existing models, a multi-level modeling approach is employed
to describe all the necessary details of region–region relations based upon topological invariants. In this approach, a set
of hierarchically topological invariants is defined based upon the boundary–boundary intersection set (BBIS) of two involved
regions. These topological invariants are classified into three levels based upon spatial set concept proposed, which include
content, dimension and separation number at the set level, the element type at the element level, and the sequence at the
integrated level. Corresponding to these hierarchical invariants, multi-level formal models of topological relations between
spatial regions are built. A practical example is provided to illustrate the use of the approach presented in this paper.
相似文献
Zhilin LiEmail: |
14.
Since maps are widely available for many areas around the globe, they provide a valuable resource to help understand other
geospatial sources such as to identify roads or to annotate buildings in imagery. To utilize the maps for understanding other
geospatial sources, one of the most valuable types of information we need from the map is the road network, because the roads
are common features used across different geospatial data sets. Specifically, the set of road intersections of the map provides
key information about the road network, which includes the location of the road junctions, the number of roads that meet at
the intersections (i.e., connectivity), and the orientations of these roads. The set of road intersections helps to identify
roads on imagery by serving as initial seed templates to locate road pixels. Moreover, a conflation system can use the road
intersections as reference features (i.e., control point set) to align the map with other geospatial sources, such as aerial
imagery or vector data. In this paper, we present a framework for automatically and accurately extracting road intersections
from raster maps. Identifying the road intersections is difficult because raster maps typically contain much information such
as roads, symbols, characters, or even contour lines. We combine a variety of image processing and graphics recognition methods
to automatically separate roads from the raster map and then extract the road intersections. The extracted information includes
a set of road intersection positions, the road connectivity, and road orientations. For the problem of road intersection extraction,
our approach achieves over 95% precision (correctness) with over 75% recall (completeness) on average on a set of 70 raster
maps from a variety of sources.
Yao-Yi Chiang is currently a Ph.D. student at the University of Southern California (USC). He received his B.S. in Information Management from National Taiwan University in 2000 and then his M.S. degree in Computer Science from the USC in December 2004. His research interests are on the automatic fusion of geographical data. He has worked extensively on the problem of automatically utilize raster maps for understanding other geospatial sources and has wrote and co-authored several papers on automatically fusing map and imagery as well as automatic map processing. Prior to his doctoral study at USC, Yao-Yi worked as a Research Scientist for Information Sciences Institute and Geosemble Technologies. Craig A. Knoblock is a Senior Project Leader at the Information Sciences Institute and a Research Professor in Computer Science at the USC. He is also the Chief Scientist for Geosemble Technologies, which is a USC spinoff company that is commercializing work on geospatial integration. He received his Ph.D. in Computer Science from Carnegie Mellon. His current research interests include information integration, automated planning, machine learning, and constraint reasoning and the application of these techniques to geospatial data integration. He is a Fellow of the American Association of Artificial Intelligence. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center at the USC. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. degrees in Computer Science from the USC in May 1993 and August 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, geographic information system (GIS) and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems and on the editorial board of ACM Computers in Entertainment magazine. He is also a member of the steering committees of IEEE NetDB and the general co-chair of ACM GIS 2007. He serves on many conference program committees such as VLDB 2008, ACM SIGKDD 2006 to 2008, IEEE ICDE 2006 and 2008, SSTD 2005 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers. In 2001, he also received an award from the Okawa Foundations. Ching-Chien Chen is the Director of Research and Development at Geosemble Technologies. He received his Ph.D. degree in Computer Science from the USC for a dissertation that presented novel approaches to automatically align road vector data, street maps and orthoimagery. His research interests are on the fusion of geographical data, such as imagery, vector data and raster maps with open source data. His current research activities include the automatic conflation of geospatial data, automatic processing of raster maps and design of GML-enabled and GIS-related web services. Dr. Chen has a number of publications on the topic of automatic conflation of geospatial data sources. 相似文献
Ching-Chien ChenEmail: |
Yao-Yi Chiang is currently a Ph.D. student at the University of Southern California (USC). He received his B.S. in Information Management from National Taiwan University in 2000 and then his M.S. degree in Computer Science from the USC in December 2004. His research interests are on the automatic fusion of geographical data. He has worked extensively on the problem of automatically utilize raster maps for understanding other geospatial sources and has wrote and co-authored several papers on automatically fusing map and imagery as well as automatic map processing. Prior to his doctoral study at USC, Yao-Yi worked as a Research Scientist for Information Sciences Institute and Geosemble Technologies. Craig A. Knoblock is a Senior Project Leader at the Information Sciences Institute and a Research Professor in Computer Science at the USC. He is also the Chief Scientist for Geosemble Technologies, which is a USC spinoff company that is commercializing work on geospatial integration. He received his Ph.D. in Computer Science from Carnegie Mellon. His current research interests include information integration, automated planning, machine learning, and constraint reasoning and the application of these techniques to geospatial data integration. He is a Fellow of the American Association of Artificial Intelligence. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center at the USC. He received his B.S. in Computer Engineering from Sharif University of Technology in 1989 and then his M.S. and Ph.D. degrees in Computer Science from the USC in May 1993 and August 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, geographic information system (GIS) and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems and on the editorial board of ACM Computers in Entertainment magazine. He is also a member of the steering committees of IEEE NetDB and the general co-chair of ACM GIS 2007. He serves on many conference program committees such as VLDB 2008, ACM SIGKDD 2006 to 2008, IEEE ICDE 2006 and 2008, SSTD 2005 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers. In 2001, he also received an award from the Okawa Foundations. Ching-Chien Chen is the Director of Research and Development at Geosemble Technologies. He received his Ph.D. degree in Computer Science from the USC for a dissertation that presented novel approaches to automatically align road vector data, street maps and orthoimagery. His research interests are on the fusion of geographical data, such as imagery, vector data and raster maps with open source data. His current research activities include the automatic conflation of geospatial data, automatic processing of raster maps and design of GML-enabled and GIS-related web services. Dr. Chen has a number of publications on the topic of automatic conflation of geospatial data sources. 相似文献
15.
Recent growth of geospatial information online has made it possible to access various maps and orthoimagery. Conflating these
maps and imagery can create images that combine the visual appeal of imagery with the attribution information from maps. The
existing systems require human intervention to conflate maps with imagery. We present a novel approach that utilizes vector
datasets as “glue” to automatically conflate street maps with imagery. First, our approach extracts road intersections from
imagery and maps as control points. Then, it aligns the two point sets by computing the matched point pattern. Finally, it
aligns maps with imagery based on the matched pattern. The experiments show that our approach can conflate various maps with
imagery, such that in our experiments on TIGER-maps covering part of St. Louis county, MO, 85.2% of the conflated map roads
are within 10.8 m from the actual roads compared to 51.7% for the original and georeferenced TIGER-map roads.
Ching-Chien Chen is the Director of Research and Development at Geosemble Technologies. He received his Ph.D. degree in Computer Science from the University of Southern California for a dissertation that presented novel approaches to automatically align road vector data, street maps and orthoimagery. His research interests are on the fusion of geographical data, such as imagery, vector data and raster maps with open source data. His current research activities include the automatic conflation of geospatial data, automatic processing of raster maps and design of GML-enabled and GIS-related web services. Dr. Chen has a number of publications on the topic of automatic conflation of geospatial data sources. Craig Knoblock is a Senior Project Leader at the Information Sciences Institute and a Research Professor in Computer Science at the University of Southern California (USC). He is also the Chief Scientist for Geosemble Technologies, which is a USC spinoff company that is commercializing work on geospatial integration. He received his Ph.D. in Computer Science from Carnegie Mellon. His current research interests include information integration, automated planning, machine learning, and constraint reasoning and the application of these techniques to geospatial data integration. He is a Fellow of the American Association of Artificial Intelligence. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his B.S. degree in Computer Engineering from Sharif University of Technology in 1989 and his M.S. and Ph.D. degree in Computer Science from the University of Southern California in 1993 and 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems (TPDS) and on the editorial board of ACM Computers in Entertainment magazine. He is also in the steering committee of IEEE NetDB and ACM GIS. He serves on many conference program committees such as ACM SIGKDD 2006, IEEE ICDE 2006, ACM CIKM 2005, SSTD 2005 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations. 相似文献
Cyrus ShahabiEmail: |
Ching-Chien Chen is the Director of Research and Development at Geosemble Technologies. He received his Ph.D. degree in Computer Science from the University of Southern California for a dissertation that presented novel approaches to automatically align road vector data, street maps and orthoimagery. His research interests are on the fusion of geographical data, such as imagery, vector data and raster maps with open source data. His current research activities include the automatic conflation of geospatial data, automatic processing of raster maps and design of GML-enabled and GIS-related web services. Dr. Chen has a number of publications on the topic of automatic conflation of geospatial data sources. Craig Knoblock is a Senior Project Leader at the Information Sciences Institute and a Research Professor in Computer Science at the University of Southern California (USC). He is also the Chief Scientist for Geosemble Technologies, which is a USC spinoff company that is commercializing work on geospatial integration. He received his Ph.D. in Computer Science from Carnegie Mellon. His current research interests include information integration, automated planning, machine learning, and constraint reasoning and the application of these techniques to geospatial data integration. He is a Fellow of the American Association of Artificial Intelligence. Cyrus Shahabi is currently an Associate Professor and the Director of the Information Laboratory (InfoLAB) at the Computer Science Department and also a Research Area Director at the NSF’s Integrated Media Systems Center (IMSC) at the University of Southern California. He received his B.S. degree in Computer Engineering from Sharif University of Technology in 1989 and his M.S. and Ph.D. degree in Computer Science from the University of Southern California in 1993 and 1996, respectively. He has two books and more than hundred articles, book chapters, and conference papers in the areas of databases, GIS and multimedia. Dr. Shahabi’s current research interests include Geospatial and Multidimensional Data Analysis, Peer-to-Peer Systems and Streaming Architectures. He is currently an associate editor of the IEEE Transactions on Parallel and Distributed Systems (TPDS) and on the editorial board of ACM Computers in Entertainment magazine. He is also in the steering committee of IEEE NetDB and ACM GIS. He serves on many conference program committees such as ACM SIGKDD 2006, IEEE ICDE 2006, ACM CIKM 2005, SSTD 2005 and ACM SIGMOD 2004. Dr. Shahabi is the recipient of the 2002 National Science Foundation CAREER Award and 2003 Presidential Early Career Awards for Scientists and Engineers (PECASE). In 2001, he also received an award from the Okawa Foundations. 相似文献
16.
Dimitrios K. Vassilakis Vasilis Vassalos 《Peer-to-Peer Networking and Applications》2009,2(2):109-127
We develop a new model of the interaction of rational peers in a Peer-to-Peer (P2P) network that has at its heart altruism, an intrinsic parameter reflecting peers’ inherent willingness to contribute. Two different approaches for modelling altruistic
behavior and its attendant benefit are introduced. With either approach, we use Game Theoretic analysis to calculate Nash
equilibria and predict peer behavior in terms of individual contribution. We consider the cases of P2P networks of peers that
(i) have homogeneous altruism levels or (ii) have heterogeneous altruism levels, but with known probability distributions.
We find that, under the effects of altruism, a substantial fraction of peers will contribute when altruism levels are within
certain intervals, even though no incentive mechanism is used. Our results corroborate empirical evidence of large P2P networks
surviving or even flourishing without or with barely functioning incentive mechanisms. We also enhance the model with a simple
but powerful incentive scheme to limit free-riding and increase contribution to the network, and show that the particular
incentive scheme on networks with altruistic peers achieves its goal.
Dimitrios K. Vassilakis 2005–today: PhD candidate in the Informatics Department of the Athens University of Economics and Business (AUEB). Research areas: Operations Research (OR), Game Theory, economic models and applications of Game Theory on the internet (anti-spam, P2P networks), applications of OR on electricity scheduling. Vasilis Vassalos 2003–today: Assistant Professor in the Informatics Department of the Athens University of Economics and Business (AUEB). 1999–2003: assistant professor in the Information Systems Group of Information, Operations and Management Sciences (IOMS) Department in the Stern School of Business at New York University. Research areas: databases, Web-based information systems and middleware development, generation of user interfaces and Web services for semistructured data sources, integration of mobile data sources, XML query processing, digital libraries. 相似文献
Vasilis VassalosEmail: URL: http://wim.aueb.gr/vassalos |
Dimitrios K. Vassilakis 2005–today: PhD candidate in the Informatics Department of the Athens University of Economics and Business (AUEB). Research areas: Operations Research (OR), Game Theory, economic models and applications of Game Theory on the internet (anti-spam, P2P networks), applications of OR on electricity scheduling. Vasilis Vassalos 2003–today: Assistant Professor in the Informatics Department of the Athens University of Economics and Business (AUEB). 1999–2003: assistant professor in the Information Systems Group of Information, Operations and Management Sciences (IOMS) Department in the Stern School of Business at New York University. Research areas: databases, Web-based information systems and middleware development, generation of user interfaces and Web services for semistructured data sources, integration of mobile data sources, XML query processing, digital libraries. 相似文献
17.
User defined topological predicates in database systems 总被引:1,自引:0,他引:1
Current database systems cannot only store standard data like integer\underline{integer}, string\underline{string}, and real\underline{real} values, but also spatial data like points\underline{points}, lines\underline{lines}, and regions\underline{regions}. The importance of topological relationships between spatial objects has been recognized a long time ago. Using the well
known 9-intersection model for describing such relationships, a lot of different topological relationships can be distinguished.
For the query language of a database system it is not desirable to have such a large number of topological predicates. Particularly
the query language should not be extended by a lot of predicate names. It is desirable to build new relationships from existing
ones, for example to coarse the granularity. This paper describes how a database system user can define and use her own topological
predicates. We show algorithms for computing such predicates in an efficient way. Last, we compare these general versions
with specialized implementations of topological predicates. 相似文献
18.
Thomas Repantis Yannis Drougas Vana Kalogeraki 《Peer-to-Peer Networking and Applications》2009,2(1):60-74
Providing real-time and QoS support to stream processing applications running on top of large-scale overlays is challenging
due to the inherent heterogeneity and resource limitations of the nodes and the multiple QoS demands of the applications that
must concurrently be met. In this paper we propose an integrated adaptive component composition and load balancing mechanism
that (1) allows the composition of distributed stream processing applications on the fly across a large-scale system, while
satisfying their QoS demands and distributing the load fairly on the resources, and (2) adapts dynamically to changes in the
resource utilization or the QoS requirements of the applications. Our extensive experimental results using both simulations
as well as a prototype deployment illustrate the efficiency, performance and scalability of our approach.
Thomas Repantis is a PhD candidate at the Computer Science and Engineering Department of the University of California, Riverside. His research interests lie in the area of distributed systems, distributed stream processing systems, middleware, peer-to-peer systems, pervasive and cluster computing. He holds an MSc from the University of California, Riverside and a Diploma from the University of Patras, Greece, and has interned with IBM Research, Intel Research and Hewlett-Packard. Yannis Drougas is currently a Ph.D. student in the Department of Computer Science and Engineering at University of California, Riverside. He received the Diploma in Electrical and Computer Engineering from Technical University of Crete, Greece in 2003. His research interests include peer-to-peer systems, real-time systems, stream processing systems, resource management and sensor networks. Vana Kalogeraki is currently an Associate Professor in the Department of Computer Science and Engineering at the University of California, Riverside. She received the Ph.D. in Electrical and Computer Engineering from the University of California, Santa Barbara, in 2000. Previously she was an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Riverside (2002–2008) and held a Research Scientist Position at Hewlett Packard Labs in Palo Alto, CA (2001–2002). Her research interests include distributed systems, peer-to-peer systems, real-time systems, resource management and sensor networks. 相似文献
Vana Kalogeraki (Corresponding author)Email: |
Thomas Repantis is a PhD candidate at the Computer Science and Engineering Department of the University of California, Riverside. His research interests lie in the area of distributed systems, distributed stream processing systems, middleware, peer-to-peer systems, pervasive and cluster computing. He holds an MSc from the University of California, Riverside and a Diploma from the University of Patras, Greece, and has interned with IBM Research, Intel Research and Hewlett-Packard. Yannis Drougas is currently a Ph.D. student in the Department of Computer Science and Engineering at University of California, Riverside. He received the Diploma in Electrical and Computer Engineering from Technical University of Crete, Greece in 2003. His research interests include peer-to-peer systems, real-time systems, stream processing systems, resource management and sensor networks. Vana Kalogeraki is currently an Associate Professor in the Department of Computer Science and Engineering at the University of California, Riverside. She received the Ph.D. in Electrical and Computer Engineering from the University of California, Santa Barbara, in 2000. Previously she was an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Riverside (2002–2008) and held a Research Scientist Position at Hewlett Packard Labs in Palo Alto, CA (2001–2002). Her research interests include distributed systems, peer-to-peer systems, real-time systems, resource management and sensor networks. 相似文献
19.
This paper investigates the control of parameterized discrete event systems when specifications are given in terms of predicates
and satisfy a similarity assumption. This study is motivated by a weakness in current synthesis methods that do not scale
well to huge systems. For systems consisting of similar processes under total or partial observation, conditions are given
to deduce properties of a system of n processes (arbitrary size) from properties of a system of n
0 processes (bounded size), with n ≥ n
0. Furthermore, it is shown how to infer a control policy for the former from the latter’s, while taking into account interconnections
between processes.
Hans Bherer is the research lead of the Natural Language Processing and Knowledge Representation group at xtranormal Inc. He is pursuing a Ph.D. in software engineering at Université Laval in Canada. His research interests include discrete event systems, complexity, reasoning and logical formalisms. Bherer has a B.Sc. and an M.Sc. in mathematics from Université Laval. Jules Desharnais received the B.Sc. and M.Sc. degrees in computer science from Université Laval in 1983 and 1985, respectively, and the Ph.D. degree in computer science from McGill University in 1989. He is currently a professor of computer science at Université Laval. His main research interest is that of the mathematics of program construction, with ongoing work both on the development of mathematics (mostly Kleene algebra) and on applications to the derivation of programs and controllers. Richard St-Denis received the B.Sc. and M.Sc. degrees in computer science from Université de Montréal in 1975 and 1977, respectively, and the Ph.D. degree in applied sciences from école Polytechnique de Montréal in 1992. He is currently a professor of computer science at Université de Sherbrooke, where his research interests include reactive systems, discrete event systems and software engineering. He has published a book in French on programming with the Sparc assembly language. 相似文献
Richard St-Denis (Corresponding author)Email: |
Hans Bherer is the research lead of the Natural Language Processing and Knowledge Representation group at xtranormal Inc. He is pursuing a Ph.D. in software engineering at Université Laval in Canada. His research interests include discrete event systems, complexity, reasoning and logical formalisms. Bherer has a B.Sc. and an M.Sc. in mathematics from Université Laval. Jules Desharnais received the B.Sc. and M.Sc. degrees in computer science from Université Laval in 1983 and 1985, respectively, and the Ph.D. degree in computer science from McGill University in 1989. He is currently a professor of computer science at Université Laval. His main research interest is that of the mathematics of program construction, with ongoing work both on the development of mathematics (mostly Kleene algebra) and on applications to the derivation of programs and controllers. Richard St-Denis received the B.Sc. and M.Sc. degrees in computer science from Université de Montréal in 1975 and 1977, respectively, and the Ph.D. degree in applied sciences from école Polytechnique de Montréal in 1992. He is currently a professor of computer science at Université de Sherbrooke, where his research interests include reactive systems, discrete event systems and software engineering. He has published a book in French on programming with the Sparc assembly language. 相似文献
20.
Semi-supervised discriminative classification with application to tumorous tissues segmentation of MR brain images 总被引:1,自引:1,他引:0
Yangqiu Song Changshui Zhang Jianguo Lee Fei Wang Shiming Xiang Dan Zhang 《Pattern Analysis & Applications》2009,12(2):99-115
Due to the large data size of 3D MR brain images and the blurry boundary of the pathological tissues, tumor segmentation work
is difficult. This paper introduces a discriminative classification algorithm for semi-automated segmentation of brain tumorous
tissues. The classifier uses interactive hints to obtain models to classify normal and tumor tissues. A non-parametric Bayesian
Gaussian random field in the semi-supervised mode is implemented. Our approach uses both labeled data and a subset of unlabeled
data sampling from 2D/3D images for training the model. Fast algorithm is also developed. Experiments show that our approach
produces satisfactory segmentation results comparing to the manually labeled results by experts.
Yangqiu Song received his B.S. degree from Department of Automation, Tsinghua University, China, in 2003. He is currently a Ph.D. candidate in Department of Automation, Tsinghua University. His research interests focus on machine learning and its applications. Changshui Zhang received his B.S. degree in Mathematics from Peking University, China, in 1986, and Ph.D. degree from Department of Automation, Tsinghua University in 1992. He is currently a professor of Department of Automation, Tsinghua University. He is an Associate Editor of the journal Pattern Recognition. His interests include artificial intelligence, image processing, pattern recognition, machine learning, evolutionary computation and complex system analysis, etc. Jianguo Lee received his B.S. degree from Department of Automatic Control, Huazhong University of Science and Technology (HUST), China, in 2001 and Ph.D. degree in Department of Automation, Tsinghua University in 2006. He is currently a researcher in Intel China Reasearch Center. His research interests focus on machine learning and its applications. Fei Wang is a Ph.D. candidate from Department of Automation, Tsinghua University, Beijing, China. His main research interests include machine learning, data mining, and pattern recognition. Shiming Xiang received his B.S. degree from Department of Mathematics of Chongqing Normal University, China, in 1993 and M.S. degree from Department of Mechanics and Mathematics of Chongqing University, China, in 1996 and Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences, China, in 2004. He is currently a postdoctoral scholar in Department of Automation, Tsinghua University. His interests include computer vision, pattern recognition, machine learning, etc. Dan Zhang received his B.S. degree in Electronic and Information Engineering from Nanjing University of Posts and Telecommunications in 2005. He is now a Master candidate from Department of Automation, Tsinghua University, Beijing, China. His research interests include pattern recognition, machine learning, and blind signal separation. 相似文献
Changshui ZhangEmail: |
Yangqiu Song received his B.S. degree from Department of Automation, Tsinghua University, China, in 2003. He is currently a Ph.D. candidate in Department of Automation, Tsinghua University. His research interests focus on machine learning and its applications. Changshui Zhang received his B.S. degree in Mathematics from Peking University, China, in 1986, and Ph.D. degree from Department of Automation, Tsinghua University in 1992. He is currently a professor of Department of Automation, Tsinghua University. He is an Associate Editor of the journal Pattern Recognition. His interests include artificial intelligence, image processing, pattern recognition, machine learning, evolutionary computation and complex system analysis, etc. Jianguo Lee received his B.S. degree from Department of Automatic Control, Huazhong University of Science and Technology (HUST), China, in 2001 and Ph.D. degree in Department of Automation, Tsinghua University in 2006. He is currently a researcher in Intel China Reasearch Center. His research interests focus on machine learning and its applications. Fei Wang is a Ph.D. candidate from Department of Automation, Tsinghua University, Beijing, China. His main research interests include machine learning, data mining, and pattern recognition. Shiming Xiang received his B.S. degree from Department of Mathematics of Chongqing Normal University, China, in 1993 and M.S. degree from Department of Mechanics and Mathematics of Chongqing University, China, in 1996 and Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences, China, in 2004. He is currently a postdoctoral scholar in Department of Automation, Tsinghua University. His interests include computer vision, pattern recognition, machine learning, etc. Dan Zhang received his B.S. degree in Electronic and Information Engineering from Nanjing University of Posts and Telecommunications in 2005. He is now a Master candidate from Department of Automation, Tsinghua University, Beijing, China. His research interests include pattern recognition, machine learning, and blind signal separation. 相似文献