A Type of Triangular Ball Surface and its Properties

A new type of bivariate generalized Ball basis function on a triangle is presented for free-form surface design.Some properties of the basis function are given,then degree elevation,recursive evaluation and some other properties of the generalized Ball surfaces are also derived.It is shown that the proposed recursive evaluation algorithm is more efficient than those of the old surfaces.     

Scheduling algorithms based on weakly hard real-time constraints

The problem of scheduling weakly hard real-time tasks is addressed in this paper.The paper first analyzes the characters of μ-pattern and weakly hard real-time constraints,then,presents two scheduling algorithms,Meet Any Algorithm and Meet Row Algorithm,for weakly hard real-time systems.Different from traditional algorithms used to guarantee deadlines,MeetAny Algorithm and Meet Row Algorithm can guarantee both deadlines and constraints.Meet Any Algorithm and Meet Row Algorithm try to find out the probabilities of tasks breaking constraints and increase task‘s priority in advance,but not till the last moment.Simulation results show that these two algorithms are better than other scheduling algorithms dealing with constraints and can largely decrease worst-case computation time of real-time tasks.     

Realistic modeling and animation of human body based on scanned data

In this paper we propose a novel method for building animation model of real human body from surface scanned data. The human model is represented by a triangular mesh and described as a layered geometric model. The model consists of two layers: the control skeleton generating body animation from motion capture data, and the simplified surface model providing an efficient representation of the skin surface shape. The skeleton is generated automatically from surface scanned data using the feature extraction, and then a point-to-line mapping is used to map the surface model onto the underlying skeleton. The resulting model enables real-time and smooth animation by manipulation of the skeleton while maintaining the surface detail. Compared with earlier approach, the principal advantages of our approach are the automated generation of body control skeletons from the scanned data for real-time animation, and the automatic mapping and animation of the captured human surface shape. The human model constructed in this work can be used for applications of ergonomic design,garment CAD, real-time simulating humans in virtual reality environment and so on.     

Robust control design of a class of nonlinear systems in polynomial lower-triangular form

This paper investigates the problem of global robust stabilization for a wide class of nonlinear systems, called polynomial lower-triangular form (pLTF), which expands LTF to a more general case. The aim is explicitly constructing the smooth controller for the class of systems with static uncertainties, by adding and modifying a power integrator in a recursive manner. The pLTF relaxes the restrictions on the structure of the normal LTF and enlarges the family of systems that are stabilizable. Examples are also provided to show the practical usage of this class of systems and the effectiveness of the design method. Recommended by Editorial Board member Hyungbo Shim under the direction of Editor Jae Weon Choi. Bing Wang received the B.S. degree from the Huazhong University of Science and Technology, and the Ph.D. degree from the University of Science and Technology of China, in 1998 and 2006, respectively. He is currently working in College of Electrical Engineering, Hohai University. His research interests include robust control, nonlinear control and power systems. Haibo Ji received the B.S. and Ph.D. degrees in Mechanical Engineering from ZheJiang University and Beijing University in 1984 and 1990 respectively. He is currently a Professor in the Dept. of Automation, USTC. His research interests include nonlinear control and adaptive control. Jin Zhu received the B.S. and Ph.D. degrees in Control Science and Engineering from University of Science & Technology of Chinain 2001 and 2006 respectively. He is currently a Post-doc in Han-Yang University, Korea. His research interests include Markovian jump systems and nonlinear control.     

Oscillation amplitude-controlled resonant accelerometer design using a reference tracking automatic gain control

In this paper, it is presented a novel approach for the self-sustained resonant accelerometer design, which takes advantages of an automatic gain control in achieving stabilized oscillation dynamics. Through the proposed system modeling and loop transformation, the feedback controller is designed to maintain uniform oscillation amplitude under dynamic input accelerations. The fabrication process for the mechanical structure is illustrated in brief. Computer simulation and experimental results show the feasibility of the proposed accelerometer design, which is applicable to a control grade inertial sense system. Recommended by Editorial Board member Dong Hwan Kim under the direction of Editor Hyun Seok Yang. This work was supported by the BK21 Project ST·IT Fusion Engineering program in Konkuk University, 2008. This work was supported by the Korea Foundation for International Cooperation of Science & Technology(KICOS) through a grant provided by the Korean Ministry of Education, Science & Technology(MEST) in 2008 (No. K20601000001). Authors also thank to Dr. B.-L. Lee for the help in structure manufacturing. Sangkyung Sung is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the M.S and Ph.D. degrees in Electrical Engineering from Seoul National University in 1998 and 2003, respectively. His research interests include inertial sensors, avionic system hardware, navigation filter, and intelligent vehicle systems. Chang-Joo Kim is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aeronautical Engineering from Seoul National University in 1991. His research interests include nonlinear optimal control, helicopter flight mechanics, and helicopter system design. Young Jae Lee is a Professor of the Department of Aerospace Engineering at Konkuk University, Korea. He received the Ph.D. degree in Aerospace Engineering from the University of Texas at Austin in 1990. His research interests include integrity monitoring of GNSS signal, GBAS, RTK, attitude determination, orbit determination, and GNSS related engineering problems. Jungkeun Park is an Assistant Professor of the Department of Aerospace Engineering at Konkuk University. Dr. Park received the Ph.D. in Electrical Engineering and Computer Science from the Seoul National University in 2004. His current research interests include embedded real-time systems design, real-time operating systems, distributed embedded real-time systems and multimedia systems. Joon Goo Park is an Assistant Professor of the Department of Electronic Engineering at Gyung Book National University, Korea. He received the Ph.D. degree in School of Electrical Engineering from Seoul National University in 2001. His research interests include mobile navigation and adaptive control.     

Static extensivity analysis for λ-definable functions over lattices

We employ a static analysis to examine the extensivity (∀x:x≤f(x)) of functions defined over lattices in a λ-calculus augmented with lattice operations. The need for such a verification procedure has arisen in our work on a generator system (called Zoo) of static program-analyzers. The input to Zoo is a static analysis specification that consists of lattice definitions and function definitions over the lattices. Once the extensivity of the functions is ascertained, the generated analyzer is guaranteed to terminate when the lattices have finite-heights. The extensivity analysis consists of a sound syntax-driven deductive rules whose satisfiability check is done by a constraint solving procedure. Hyunjun Eo: He is a Ph.D. candidate of Computer Science Dept. at KAIST (Korea Advanced Institute of Science and Technology). He received his B.S. and M.S. in Computer Science from KAIST in 1996 and 1998, respectively. For 1998–2003, he was a research assistant of the National Creative Research Initiative Center for Research On Program Analysis System. His research interest has been on static program analysis, program logics, and higher-order and typed languages. He is currently working on developing a tool for automatic generation of program analyzers. Kwangkeun Yi, Ph.D.: His research interest has been on semantic-based program analysis and systems application of language technologies. After his Ph.D. from University of Illinois at Urbana-Champaign he joined the Software Principles Research Department at Bell Laboratories, where he worked on various static analysis approaches for higher-order and typed programming languages. For 1995–2003, he was a faculty member in the Department of Computer Science, Korea Advanced Institute of Science and Technology. Since Fall 2003, he has been a faculty member in the School of Computer Science and Engineering, Seoul National University. Kwang-Moo Choe, Ph.D.: He is a professor of Computer Science at Korea Advanced Institute of Science and Technology. He received his B.S. from Seoul National University in 1976, and his M.S. and Ph.D. from Korea Advanced Institute of Science and Technology in 1978 and 1984, respectively. For 1985–1986, he was a technical staff of AT&T Bell Labs at Murray Hill. His research interest is formal language theory, parallel evaluation of logic programs, and optimizing compilers.     

Preference update for e-commerce applications: Model,language, and processing

It is likely that customers issue requests based on out-of-date information in e-commerce application systems. Hence, the transaction failure rates would increase greatly. In this paper, we present a preference update model to address this problem. A preference update is an extended SQL update statement where a user can request the desired number of target data items by specifying multiple preferences. Moreover, the preference update allows easy extraction of criteria from a set of concurrent requests and, hence, optimal decisions for the data assignments can be made. We propose a group evaluation strategy for preference update processing in a multidatabase environment. The experimental results show that the group evaluation can effectively increase the customer satisfaction level with acceptable cost. Peng Li is the Chief Software Architect of didiom LLC. Before that, he was a visiting assistant professor of computer science department in Western Kentucky University. He received his Ph.D. degree of computer science from the University of Texas at Dallas. He also holds a B.Sc. and M.S. in Computer Science from the Renmin University of China. His research interests include database systems, database security, transaction processing, distributed and Internet computer and E-commerce. Manghui Tu received a Bachelor degree of Science from Wuhan University, P.R. China in 1996, and a Master Degree in Computer Science from the University of Texas at Dallas 2001. He is currently working toward the PhD degree in the Department of Computer Science at the University of Texas at Dallas. Mr. Tu’s research interests include distributed systems, grid computing, information security, mobile computing, and scientific computing. His PhD research work focus on the data management in secure and high performance data grid. He is a student member of the IEEE. I-Ling Yen received her BS degree from Tsing-Hua University, Taiwan, and her MS and PhD degrees in Computer Science from the University of Houston. She is currently an Associate Professor of Computer Science at the University of Texas at Dallas. Dr. Yen’s research interests include fault-tolerant computing, security systems and algorithms, distributed systems, Internet technologies, E-commerce, and self-stabilizing systems. She had published over 100 technical papers in these research areas and received many research awards from NSF, DOD, NASA, and several industry companies. She has served as Program Committee member for many conferences and Program Chair/Co-Chair for the IEEE Symposium on Application-Specific Software and System Engineering & Technology, IEEE High Assurance Systems Engineering Symposium, IEEE International Computer Software and Applications Conference, and IEEE International Symposium on Autonomous Decentralized Systems. She is a member of the IEEE. Zhonghang Xia received the B.S. degree in applied mathematics from Dalian University of Technology in 1990, the M.S. degree in Operations Research from Qufu Normal University in 1993, and the Ph.D. degree in computer science from the University of Texas at Dallas in 2004. He is now an assistant professor in the Department of Computer Science, Western Kentucky University, Bowling Green, KY. His research interests are in the area of multimedia computing and networking, distributed systems, and data mining.     

Multi economic agent interaction for optimizing the aggregate utility of grid users in computational grid

This paper investigates the interactions between agents representing grid users and the providers of grid resources to maximize the aggregate utilities of all grid users in computational grid. It proposes a price-based resource allocation model to achieve maximized utility of grid users and providers in computational grid. Existing distributed resource allocation schemes assume the resource provider to be capable of measuring user’s resource demand, calculating and communicating price, none of which actually exists in reality. This paper addresses these challenges as follows. First, the grid user utility is defined as a function of the grid user’s the resource units allocated. We formalize resource allocation using nonlinear optimization theory, which incorporates both grid resource capacity constraint and the job complete times. An optimal solution maximizes the aggregate utilities of all grid users. Second, this paper proposes a new optimization-based grid resource pricing algorithm for allocating resources to grid users while maximizing the revenue of grid providers. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme. Li Chunlin received the ME in computer science from Wuhan Transportation University in 2000, and PhD degree in Computer Software and Theory from Huazhong University of Science and Technology in 2003. She now is an associate professor of Computer Science in Wuhan University of Technology. Her research interests include computational grid, distributed computing and mobile agent. She has published over 15 papers in international journals. Li Layuan received the BE degree in Communication Engineering from Harbin Institute of Military Engineering, China in 1970 and the ME degree in Communication and Electrical Systems from Huazhong University of Science and Technology, China in 1982. Since 1982, he has been with the Wuhan University of Technology, China, where he is currently a Professor and PhD tutor of Computer Science, and Editor in Chief of the Journal of WUT. He is Director of International Society of High-Technol and Paper Reviewer of IEEE INFOCOM, ICCC and ISRSDC. His research interests include high speed computer networks, protocol engineering and image processing. Professor Li has published over 150 technical papers and is the author of six books. He also was awarded the National Special Prize by the Chinese Government in 1993.     

A metamodel for modeling system features and their refinement, constraint and interaction relationships

This paper presents a metamodel for modeling system features and relationships between features. The underlying idea of this metamodel is to employ features as first-class entities in the problem space of software and to improve the customization of software by explicitly specifying both static and dynamic dependencies between system features. In this metamodel, features are organized as hierarchy structures by the refinement relationships, static dependencies between features are specified by the constraint relationships, and dynamic dependencies between features are captured by the interaction relationships. A first-order logic based method is proposed to formalize constraints and to verify constraints and customization. This paper also presents a framework for interaction classification, and an informal mapping between interactions and constraints through constraint semantics. Hong Mei received the BSc and MSc degrees in computer science from the Nanjing University of Aeronautics and Astronautics (NUAA), China, in 1984 and 1987, respectively, and the PhD degree in computer science from the Shanghai Jiao Tong University in 1992. He is currently a professor of Computer Science at the Peking University, China. His current research interests include Software Engineering and Software Engineering Environment, Software Reuse and Software Component Technology, Distributed Object Technology, and Programming Language. He has published more than 100 technical papers. Wei Zhang received the BSc in Engineering Thermophysics and the MSc in Computer Science from the Nanjing University of Aeronautics and Astronautics (NUAA), China, in 1999 and 2002, respectively. He is currently a PhD student at the School of Electronics Engineering and Computer Science of the Peking University, China. His research interests include feature-oriented requirements modeling, feature-driven software architecture design and feature-oriented software reuse. Haiyan Zhao received both the BSc and the MSc degree in Computer Science from the Peking Univeristy, China, and the Ph.D degree in Information Engineering from the University of Tokyo, Japan. She is currently an associate professor of Computer Science at the Peking University, China. Her research interests include Software Reuse, Domain Engineering, Domain Specific Languange and Program Transformation.     

An Algorithm Based on Tabu Search for Satisfiability Problem

In this paper,a computationally effective algorithm based on tabu search for solving the satisfiability problem(TSSAT)is proposed.Some novel and efficient heuristic strategies for generating candidate neighborhood of the curred assignment and selecting varibables to be flipped are presented. Especially,the aspiration criterion and tabu list tructure of TSSAT are different from those of traditional tabu search.Computational experiments on a class of problem insteances show that,TSSAT,in a reasonable amount of computer time ,yields better results than Novelty which is currently among the fastest known.Therefore TSSAT is feasible and effective.     

Improving retrieval performance by region constraints and relevance feedback

In this paper, region features and relevance feedback are used to improve the performance of CBIR. Unlike existing region-based approaches where either individual regions are used or only simple spatial layout is modeled, the proposed approach simultaneously models both region properties and their spatial relationships in a probabilistic framework. Furthermore, the retrieval performance is improved by an adaptive filter based relevance feedback. To illustrate the performance of the proposed approach, extensive experiments have been carried out on a large heterogeneous image collection with 17,000 images, which render promising results on a wide variety of queries.     

A study of the model and algorithms for handling location-dependent continuous queries

Advances in wireless and mobile computing environments allow a mobile user to access a wide range of applications. For example, mobile users may want to retrieve data about unfamiliar places or local life styles related to their location. These queries are called location-dependent queries. Furthermore, a mobile user may be interested in getting the query results repeatedly, which is called location-dependent continuous querying. This continuous query emanating from a mobile user may retrieve information from a single-zone (single-ZQ) or from multiple neighbouring zones (multiple-ZQ). We consider the problem of handling location-dependent continuous queries with the main emphasis on reducing communication costs and making sure that the user gets correct current-query result. The key contributions of this paper include: (1) Proposing a hierarchical database framework (tree architecture and supporting continuous query algorithm) for handling location-dependent continuous queries. (2) Analysing the flexibility of this framework for handling queries related to single-ZQ or multiple-ZQ and propose intelligent selective placement of location-dependent databases. (3) Proposing an intelligent selective replication algorithm to facilitate time- and space-efficient processing of location-dependent continuous queries retrieving single-ZQ information. (4) Demonstrating, using simulation, the significance of our intelligent selective placement and selective replication model in terms of communication cost and storage constraints, considering various types of queries. Manish Gupta received his B.E. degree in Electrical Engineering from Govindram Sakseria Institute of Technology & Sciences, India, in 1997 and his M.S. degree in Computer Science from University of Texas at Dallas in 2002. He is currently working toward his Ph.D. degree in the Department of Computer Science at University of Texas at Dallas. His current research focuses on AI-based software synthesis and testing. His other research interests include mobile computing, aspect-oriented programming and model checking. Manghui Tu received a Bachelor degree of Science from Wuhan University, P.R. China, in 1996, and a Master's Degree in Computer Science from the University of Texas at Dallas 2001. He is currently working toward the Ph.D. degree in the Department of Computer Science at the University of Texas at Dallas. Mr. Tu's research interests include distributed systems, wireless communications, mobile computing, and reliability and performance analysis. His Ph.D. research work focuses on the dependent and secure data replication and placement issues in network-centric systems. Latifur R. Khan has been an Assistant Professor of Computer Science department at University of Texas at Dallas since September 2000. He received his Ph.D. and M.S. degrees in Computer Science from University of Southern California (USC) in August 2000 and December 1996, respectively. He obtained his B.Sc. degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, in November of 1993. Professor Khan is currently supported by grants from the National Science Foundation (NSF), Texas Instruments, Alcatel, USA, and has been awarded the Sun Equipment Grant. Dr. Khan has more than 50 articles, book chapters and conference papers focusing in the areas of database systems, multimedia information management and data mining in bio-informatics and intrusion detection. Professor Khan has also served as a referee for database journals, conferences (e.g. IEEE TKDE, KAIS, ADL, VLDB) and he is currently serving as a program committee member for the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD2005), ACM 14th Conference on Information and Knowledge Management (CIKM 2005), International Conference on Database and Expert Systems Applications DEXA 2005 and International Conference on Cooperative Information Systems (CoopIS 2005), and is program chair of ACM SIGKDD International Workshop on Multimedia Data Mining, 2004. Farokh Bastani received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Bombay, and the M.S. and Ph.D. degrees in Computer Science from the University of California, Berkeley. He is currently a Professor of Computer Science at the University of Texas at Dallas. Dr. Bastani's research interests include various aspects of the ultrahigh dependable systems, especially automated software synthesis and testing, embedded real-time process-control and telecommunications systems and high-assurance systems engineering. Dr. Bastani was the Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering (IEEE-TKDE). He is currently an emeritus EIC of IEEE-TKDE and is on the editorial board of the International Journal of Artificial Intelligence Tools, the International Journal of Knowledge and Information Systems and the Springer-Verlag series on Knowledge and Information Management. He was the program cochair of the 1997 IEEE Symposium on Reliable Distributed Systems, 1998 IEEE International Symposium on Software Reliability Engineering, 1999 IEEE Knowledge and Data Engineering Workshop, 1999 International Symposium on Autonomous Decentralised Systems, and the program chair of the 1995 IEEE International Conference on Tools with Artificial Intelligence. He has been on the program and steering committees of several conferences and workshops and on the editorial boards of the IEEE Transactions on Software Engineering, IEEE Transactions on Knowledge and Data Engineering and the Oxford University Press High Integrity Systems Journal. I-Ling Yen received her B.S. degree from Tsing-Hua University, Taiwan, and her M.S. and Ph.D. degrees in Computer Science from the University of Houston. She is currently an Associate Professor of Computer Science at University of Texas at Dallas. Dr. Yen's research interests include fault-tolerant computing, security systems and algorithms, distributed systems, Internet technologies, E-commerce and self-stabilising systems. She has published over 100 technical papers in these research areas and received many research awards from NSF, DOD, NASA and several industry companies. She has served as Program Committee member for many conferences and Program Chair/Cochair for the IEEE Symposium on Application-Specific Software and System Engineering & Technology, IEEE High Assurance Systems Engineering Symposium, IEEE International Computer Software and Applications Conference, and IEEE International Symposium on Autonomous Decentralized Systems. She has also served as a guest editor for a theme issue of IEEE Computer devoted to high-assurance systems.     

A selective attention-based contextual perception approach for a humanoid robot

A humanoid robot is always flooded by sensed information when sensing the environment, and it usually needs significant time to compute and process the sensed information. In this paper, a selective attention-based contextual perception approach was proposed for humanoid robots to sense the environment with high efficiency. First, the connotation of attention window (AW) is extended to make a more general and abstract definition of AW, and its four kinds of operations and state transformations are also discussed. Second, the attention control policies are described, which integrate intensionguided perceptual objects selection and distractor inhibition, and can deal with emergent issues. Distractor inhibition is used to filter unrelated information. Last, attention policies are viewed as the robot’s perceptual modes, which can control and adjust the perception efficiency. The experimental results show that the presented approach can promote the perceptual efficiency significantly, and the perceptual cost can be effectively controlled through adopting different attention policies.     

BCL—3：Aigh Performance Basic Communication Protocol for Commodity Superserver DAWNING—3000

This paper introduces the design and implemetation of BCL-3,a high performance low-level communication software running on a cluster of SMPs(CLUMPS) called DAWNING-3000,BCL-3 provides flexible and sufficient functionality to fulfill the communication requirements of fundamental system software developed for DAWNING-3000 while guaranteeing security,scalability,and reliability,Important features of BCL-3 are presented in the paper,including special support for SMP and heterogeneous network environment,semiuser-level communication,reliable and ordered data transfer and scalable flow control,The performance evaluation of BCL-3 over Myrinet is also given.     

Modeling and stability analysis of social foraging swarms in multi-obstacle environment

In this article we specify an individual-based foraging swarm (i.e., group of agents) model with individuals that move in an n-dimensional multi-obstacle environment. The motion of each individual (i) is determined by three factors: i) attraction to the local object position (xˉio+ ) which is decided by the local information about the individuals’ position that individual i can find; ii) repulsion from the other individuals on short distances; and iii) attraction to the global object position (xgoal ) or repulsion from the obstacles in the environment. The emergent behavior of the swarm motion is the result of a balance between inter-individual interaction and the simultaneous interactions of the swarm members with their environment. We study the stability properties of the collective behavior of the swarm based on Lyapunov stability theory. The simulations show that the swarm can converge to goal regions and diverge from obstacle regions of the environment while maintaining cohesive.     

Generation of Discrete Bicubic G^1 B-Spline Ship Hullform Surfaces from a Given Curve Network Using Virtual Iso-Parametric Curves

We propose a method that automatically generates discrete bicubic G^1 continuous B-spline surfaces that interpolate the curve network of a ship huliform.First,the curves in the network are classified into two types;boundary curves and ＂reference curves＂,The boundary curves correspond to a set of rectangular（or triangular）topological type that can be representes with tensot-product （or degenerate）B-spline surface patches.Next,in the interior of the patches,surface fitting points and cross boundary derivatives are estimated from the reference curves by constructing ＂virtual＂isoparametric curves.Finally,a discrete G^1 continuous B-spline surface is gencrated by a surface fitting algorithm.Several smooth ship hullform surfaces generated from curve networks corresponding to actual ship hullforms demonstrate the quality of the method.     

Measuring class cohesion based on dependence analysis

Classes are the basic modules in object-oriented (OO) software, which consist of attributes and methods. Thus, in OO environment, the cohesion is mainly about the tightness of the attributes and methods of classes. This paper discusses the relationships between attributes and attributes, attributes and methods,methods and methods of a class based on dependence analysis. Then the paper presents methods to compute these dependencies. Based on these, the paper proposes a method to measure the class cohesion, which satisfies the properties that a good measurement should have. The approach overcomes the limitations of previous class cohesion measures, which consider only one or two of the three relationships in a class.     

Privacy preservation for data cubes

A range query finds the aggregated values over all selected cells of an online analytical processing (OLAP) data cube where the selection is specified by the ranges of contiguous values for each dimension. An important issue in reality is how to preserve the confidential information in individual data cells while still providing an accurate estimation of the original aggregated values for range queries. In this paper, we propose an effective solution, called the zero-sum method, to this problem. We derive theoretical formulas to analyse the performance of our method. Empirical experiments are also carried out by using analytical processing benchmark (APB) dataset from the OLAP Council. Various parameters, such as the privacy factor and the accuracy factor, have been considered and tested in the experiments. Finally, our experimental results show that there is a trade-off between privacy preservation and range query accuracy, and the zero-sum method has fulfilled three design goals: security, accuracy, and accessibility. Sam Y. Sung is an Associate Professor in the Department of Computer Science, School of Computing, National University of Singapore. He received a B.Sc. from the National Taiwan University in 1973, the M.Sc. and Ph.D. in computer science from the University of Minnesota in 1977 and 1983, respectively. He was with the University of Oklahoma and University of Memphis in the United States before joining the National University of Singapore. His research interests include information retrieval, data mining, pictorial databases and mobile computing. He has published more than 80 papers in various conferences and journals, including IEEE Transaction on Software Engineering, IEEE Transaction on Knowledge & Data Engineering, etc. Yao Liu received the B.E. degree in computer science and technology from Peking University in 1996 and the MS. degree from the Software Institute of the Chinese Science Academy in 1999. Currently, she is a Ph.D. candidate in the Department of Computer Science at the National University of Singapore. Her research interests include data warehousing, database security, data mining and high-speed networking. Hui Xiong received the B.E. degree in Automation from the University of Science and Technology of China, Hefei, China, in 1995, the M.S. degree in Computer Science from the National University of Singapore, Singapore, in 2000, and the Ph.D. degree in Computer Science from the University of Minnesota, Minneapolis, MN, USA, in 2005. He is currently an Assistant Professor of Computer Information Systems in the Management Science & Information Systems Department at Rutgers University, NJ, USA. His research interests include data mining, databases, and statistical computing with applications in bioinformatics, database security, and self-managing systems. He is a member of the IEEE Computer Society and the ACM. Peter A. Ng is currently the Chairperson and Professor of Computer Science at the University of Texas—Pan American. He received his Ph.D. from the University of Texas–Austin in 1974. Previously, he had served as the Vice President at the Fudan International Institute for Information Science and Technology, Shanghai, China, from 1999 to 2002, and the Executive Director for the Global e-Learning Project at the University of Nebraska at Omaha, 2000–2003. He was appointed as an Advisory Professor of Computer Science at Fudan University, Shanghai, China in 1999. His recent research focuses on document and information-based processing, retrieval and management. He has published many journal and conference articles in this area. He had served as the Editor-in-Chief for the Journal on Systems Integration (1991–2001) and as Advisory Editor for the Data and Knowledge Engineering Journal since 1989.     

Discovering user profiles for Web personalized recommendation

With the growing popularity of the World Wide Web, large volume of user access data has been gathered automatically by Web servers and stored in Web logs. Discovering and understanding user behavior patterns from log files can provide Web personalized recommendation services. In this paper, a novel clustering method is presented for log files called Clustering large Weblog based on Key Path Model (CWKPM), which is based on user browsing key path model, to get user behavior profiles. Compared with the previous Boolean model, key path model considers the major features of users‘ accessing to the Web: ordinal, contiguous and duplicate. Moreover, for clustering, it has fewer dimensions. The analysis and experiments show that CWKPM is an efficient and effective approach for clustering large and high-dimension Web logs.