Trip planning queries with location privacy in spatial databases

Privacy has become a major concern for the users of location-based services (LBSs) and researchers have focused on protecting user privacy for different location-based queries. In this paper, we propose techniques to protect location privacy of users for trip planning (TP) queries, a novel type of query in spatial databases. A TP query enables a user to plan a trip with the minimum travel distance, where the trip starts from a source location, goes through a sequence of points of interest (POIs) (e.g., restaurant, shopping center), and ends at a destination location. Due to privacy concerns, users may not wish to disclose their exact locations to the location-based service provider (LSP). In this paper, we present the first comprehensive solution for processing TP queries without disclosing a user’s actual source and destination locations to the LSP. Our system protects the user’s privacy by sending either a false location or a cloaked location of the user to the LSP but provides exact results of the TP queries. We develop a novel technique to refine the search space as an elliptical region using geometric properties, which is the key idea behind the efficiency of our algorithms. To further reduce the processing overhead while computing a trip from a large POI database, we present an approximation algorithm for privacy preserving TP queries. Extensive experiments show that the proposed algorithms evaluate TP queries in real time with the desired level of location privacy.     

基于对象关系数据库的移动对象数据库管理系统的研究

基于对象关系数据库设计了一个移动对象的数据模型,查询语言和相应的数据库管理系统。此系统结合GIS数据库系统能够表述移动物体和支持对运动物体的查询,从而实现基于位置的服务。本系统支持不确定性和复杂可扩展的空间结构,最后描述了这个系统的执行与实现。     

A usability-driven approach to the development of a 3D web-GIS environment

The main goal of this work is to provide an advanced visual environment where users that are not skilled for what concerns the computer science domain may compose queries related to those geographical phenomena for which the third dimension is a relevant feature. Visual queries are composed in a 3D environment accessible from the web where the users manipulate geographical objects, called 3D geometaphors. The geometaphors represent the operands of an underlying algebra characterized by a set of topological, directional and metrical operators; such operators are expressed in the query environment in terms of visual relationships between the geographical objects. The introduction of the third dimension for querying the geographical databases has challenged the authors with a number of important issues related to the area of visualization, navigation and object manipulation. According to the principles of usability engineering, the authors have built different prototypes based on a client-server architecture that have been iteratively evaluated by experts and final users in order to discover drawbacks and to improve the quality of the proposal. The result is a coordinated user-friendly 3D visual metaphor for querying GIS on the web, where all the elements needed for composing a query have a visual, easy to understand, counterpart.     

一种信息门户中基于本体的信息查询模型

提出了一种信息门户中的基于本体的信息查询模型，该模型主要由两个模块组成：基于领域本体的改进的查询模块和基于模糊本体的逐步精确的查询模块。前者对应于用户能够清楚地表达自己需要的信息，它可以基于相似度对查询结果进行排序。后者则对应于用户不能够清楚地表达自己需要的信息，它可以向用户提出查询建议，逐步精确用户的查询。     

Relevance measures for the creation of groups in an annotation system

The MADCOW annotation system supports a notion of group, facilitating focused annotations with respect to a domain. In previous work, we adopted ontologies to represent knowledge about domains, thus allowing more refined annotations to a group, and discussed how the use of ontologies facilitates the formulation of semantically significant queries for retrieving annotations on specific topics. We now expand on previous results and study two new types of measures to identify matches between users׳ interests and groups: Degree Centrality, developed for social networks to assess the quality of concepts in an ontology, and URL concordance, indicating the similarity of interests among users who annotate the same pages.     

Relating ontologies with a fuzzy information model

More people than ever before have access to information with the World Wide Web; information volume and number of users both continue to expand. Traditional search methods based on keywords are not effective, resulting in large lists of documents, many of which unrelated to users’ needs. One way to improve information retrieval is to associate meaning to users’ queries by using ontologies, knowledge bases that encode a set of concepts about one domain and their relationships. Encoding a knowledge base using one single ontology is usual, but a document collection can deal with different domains, each organized into an ontology. This work presents a novel way to represent and organize knowledge, from distinct domains, using multiple ontologies that can be related. The model allows the ontologies, as well as the relationships between concepts from distinct ontologies, to be represented independently. Additionally, fuzzy set theory techniques are employed to deal with knowledge subjectivity and uncertainty. This approach to organize knowledge and an associated query expansion method are integrated into a fuzzy model for information retrieval based on multi-related ontologies. The performance of a search engine using this model is compared with another fuzzy-based approach for information retrieval, and with the Apache Lucene search engine. Experimental results show that this model improves precision and recall measures.     

Dynamic path privacy protection framework for continuous query service over road networks

Many applications of location based services (LBSs), it is useful or even necessary to ensure that LBSs services determine their location. For continuous queries where users report their locations periodically, attackers can infer more about users’ privacy by analyzing the correlations of their query samples. The causes of path privacy problems, which emerge because the communication by different users in road network using location based services so, attacker can track continuous query information. LBSs, albeit useful and convenient, pose a serious threat to users’ path privacy as they are enticed to reveal their locations to LBS providers via their queries for location-based information. Traditional path privacy solutions designed in Euclidean space can be hardly applied to road network environment because of their ignorance of network topological properties. In this paper, we proposed a novel dynamic path privacy protection scheme for continuous query service in road networks. Our scheme also conceals DPP (Dynamic Path Privacy) users’ identities from adversaries; this is provided in initiator untraceability property of the scheme. We choose the different attack as our defending target because it is a particularly challenging attack that can be successfully launched without compromising any user or having access to any cryptographic keys. The security analysis shows that the model can effectively protect the user identity anonymous, location information and service content in LBSs. All simulation results confirm that our Dynamic Path Privacy scheme is not only more accurate than the related schemes, but also provide better locatable ratio where the highest it can be around 95 % of unknown nodes those can estimate their position. Furthermore, the scheme has good computation cost as well as communication and storage costs.Simulation results show that Dynamic Path Privacy has better performances compared to some related region based algorithms such as IAPIT scheme, half symmetric lens based localization algorithm (HSL) and sequential approximate maximum a posteriori (AMAP) estimator scheme.     

Mobile information search for location-based information

This study investigated mobile searching for location-based information by carrying out two experiments in an airport. The independent variables were user context, information type, information requirement pressure, and location-based information type. Experiment 1 compared users’ search performance in different user contexts while searching for different types of information. The results indicated that when users searched for location-based information, the average number of clicks decreased, the importance of the first search result increased, and free recall was better compared with non-location-based information searching. Experiment 2 further investigated the users’ mobile search performance under different levels of information requirement pressure. The results indicated that users under low pressure clicked more search results compared with users under high information requirement pressure. Compared to transactional query searching, when users engaged in informational and navigational queries, the average number of clicks increased, the importance of the first search result decreased, and free recall was worse. There was no significant difference in the number of clicks when users chose the first two search results during a mobile searching process for location-based information.     

空间网络数据库中最近邻查询的设计与实现

随着无线通讯技术、位置定位技术以及数据库技术的发展,使得能为移动用户提供相关的位置服务.K近邻查询是位置服务的一个重要功能.本文主要研究了空间网络数据库中的K近邻查询.以提出的集成道路网络距离与欧式距离的道路网络框架为基础,提出了一种新的KNN查询算法,通过网络扩展方法计算最近邻(NN),避免了不必要的磁盘I0s,减少了昂贵的最短路径计算,从而有效地提高了算法效率.实验结果说明,在目标点分布比较密集的情况下,算法显著优于其它的算法.     

语义虚拟环境本体可视化模型的研究

当前信息可视化所面临的一个瓶颈就是,需要一种模型来把场景图形内容和特定领域的语义信息进行有效集成,使用户可以有效地解释个性化可视化信息。基于X3D标准以及本体用本体描述语言OWL描述X3D标准,构建了一个X3D标准本体和一个映射本体来实现X3D标准本体和其他具体领域本体之间类和属性的映射,以达到丰富虚拟场景语义的目的。基于X3D标准本体和映射本体设计了语义虚拟环境本体可视化模型,从而为具体领域本体实现可视化提供了一种方法。实验结果证明了该模型的可行性。     

Integrating GI with non-GI services—showcasing interoperability in a heterogeneous service-oriented architecture

The concept of a service-oriented architecture provides a technical foundation for delivering, using, and integrating software. It can serve as an approach to integrate GIS with other, non-GIS applications. This paper presents and discusses a service-oriented architecture that embraces a GIS and an enterprise resource planning system. The two information systems make mutually required functionalities available as services. This defines the showcase for making GI and non-GI services syntactically and semantically interoperable. The services-based integration leverages open-standard interfacing and, thus, removes syntactic heterogeneity. The integration is discussed in terms of an emergency management scenario. This scenario also helps to outline challenging semantic interoperability issues. When services provided by GIS and non-GIS applications interact, the problem arises how their different conceptualizations should be mapped. This paper analyzes essential ontological distinctions for mapping conceptual schemes in GI locator services and non-GI services. It proposes a hybrid decentralized approach of concept mapping, based on a common top-level ontology.     

Location privacy: going beyond K-anonymity,cloaking and anonymizers

With many location-based services, it is implicitly assumed that the location server receives actual users locations to respond to their spatial queries. Consequently, information customized to their locations, such as nearest points of interest can be provided. However, there is a major privacy concern over sharing such sensitive information with potentially malicious servers, jeopardizing users’ private information. The anonymity- and cloaking-based approaches proposed to address this problem cannot provide stringent privacy guarantees without incurring costly computation and communication overhead. Furthermore, they require a trusted intermediate anonymizer to protect user locations during query processing. This paper proposes a fundamental approach based on private information retrieval to process range and K-nearest neighbor queries, the prevalent queries used in many location-based services, with stronger privacy guarantees compared to those of the cloaking and anonymity approaches. We performed extensive experiments on both real-world and synthetic datasets to confirm the effectiveness of our approaches.     

Development of a Temporal Extension to Query Travel Behavior Time Paths Using an Object-Oriented GIS

An essential requirement to better understand activity-based travel behavior (ABTB) at the disaggregate level is the development of a spatio-temporal model able to support queries related to activities of individuals or groups of individuals. This paper describes the development and implementation of a temporal extension to a geographic information system (GIS) object-oriented model for the modeling of the time path and the retrieval of its event chaining. In this approach, time path is formulated as a totally time ordered set composed by activity events and trip events, themselves organized into time ordered sets. As sets, the time path and its components can be searched using their respective indexes. A series of methods were built that implement temporal predicates as an interface to temporally query the database. A set of positional operator methods were also designed that transform temporal topological queries into retrieval functions based on set ordering indices. Taken together, the temporal predicates and the positional operator methods define a temporal query extension that meets the retrieval needs of an ABTB database.     

BIM reconstruction from 3D point clouds: A semantic registration approach based on multimodal optimization and architectural design knowledge

Reconstructing semantically rich building information model (BIM) from 2D images or 3D point clouds represents a research realm that is gaining increasing popularity in architecture, engineering, and construction. Researchers have found that architectural design knowledge, such as symmetry, planarity, parallelism, and orthogonality, can be utilized to improve the effectiveness of such BIM reconstruction. Following this line of enquiry, this paper aims to develop a novel semantic registration approach for complicated scenes with repetitive, irregular-shaped objects. The approach first formulates the architectural repetition as the multimodality in mathematics. Thus, the reconstruction of repetitive objects becomes a multimodal optimization (MMO) problem of registering BIM components which have accurate geometries and rich semantics. Then, the topological information about repetition and symmetry in the reconstructed BIM is recognized and regularized for BIM semantic enrichment. A university lecture hall case, consisting of 1.9 million noisy points of 293 chairs, was selected for an experiment to validate the proposed approach. Experimental results showed that a BIM was satisfactorily created (achieving about 90% precision and recall) automatically in 926.6 s; and an even more satisfactory BIM achieved 99.3% precision and 98.0% recall with detected semantic and topological information under the minimal effort of human intervention in 228.4 s. The multimodality model of repetitive objects, the repetition detection and regularization for BIM, and satisfactory reconstruction results in the presented approach can contribute to methodologies and practices in multiple disciplines related to BIM and smart city.     

Fast Compositional Queries in a Relational Grid Information Service

A Grid Information service (GIS) stores information about the resources of a distributed computing environment and answers questions about it. We have developed RGIS, a GIS system that, unlike previous efforts, is based on the relational data model. RGIS users can write SQL queries that search for complex compositions of resources that meet collective requirements. Executing these queries can be very expensive, however. In response, we have introduced three query techniques, nondeterminism, scoping, and approximation, that allow the user (and RGIS) to trade off between the query’s running time and the number of results. Herein we describe RGIS, our query techniques, and their implementation. Our evaluation shows that a meaningful tradeoff between query time and results returned is achievable, and that the tradeoff can be used to keep query time largely independent of query complexity. RGIS uses our techniques to bound query execution time. This strongly supports our general case for GIS systems based on the relational data model and RDBMSes. Effort sponsored by the National Science Foundation under Grants ANI-0093221, ACI-0112891, ANI-0301108, EIA-0130869, and EIA-0224449. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation (NSF).     

基于本体的突发事件应急服务模型研究

 通过研究本体理论,采用斯坦福大学医学院开发的七步法、本体构建工具（Protégé）和本体描述语言OWL,实现突发事件应急服务领域本体库的构建,研究突发事件应急服务本体模型（ESODM）对突发事件应急服务进行统一建模,有助于实现突发事件应急服务在语义级别上统一表达,从而使得突发事件应急服务信息具有计算机可以理解的语义,有助于解决不同应用之间的信息语义异构问题,有助于实现对突发事件应急服务信息资源的智能访问和检索,有助于解决语义层次上应急服务信息共享和交换等问题。     

Using Local Popularity of Web Resources for Geo-Ranking of Search Engine Results

Search engines retrieve and rank Web pages which are not only relevant to a query but also important or popular for the users. This popularity has been studied by analysis of the links between Web resources. Link-based page ranking models such as PageRank and HITS assign a global weight to each page regardless of its location. This popularity measurement has shown successful on general search engines. However unlike general search engines, location-based search engines should retrieve and rank higher the pages which are more popular locally. The best results for a location-based query are those which are not only relevant to the topic but also popular with or cited by local users. Current ranking models are often less effective for these queries since they are unable to estimate the local popularity. We offer a model for calculating the local popularity of Web resources using back link locations. Our model automatically assigns correct locations to the links and content and uses them to calculate new geo-rank scores for each page. The experiments show more accurate geo-ranking of search engine results when this model is used for processing location-based queries.     

Blind evaluation of location based queries using space transformation to preserve location privacy

In this paper we propose a fundamental approach to perform the class of Range and Nearest Neighbor (NN) queries, the core class of spatial queries used in location-based services, without revealing any location information about the query in order to preserve users’ private location information. The idea behind our approach is to utilize the power of one-way transformations to map the space of all objects and queries to another space and resolve spatial queries blindly in the transformed space. Traditional encryption based techniques, solutions based on the theory of private information retrieval, or the recently proposed anonymity and cloaking based approaches cannot provide stringent privacy guarantees without incurring costly computation and/or communication overhead. In contrast, we propose efficient algorithms to evaluate KNN and range queries privately in the Hilbert transformed space. We also propose a dual curve query resolution technique which further reduces the costs of performing range and KNN queries using a single Hilbert curve. We experimentally evaluate the performance of our proposed range and KNN query processing techniques and verify the strong level of privacy achieved with acceptable computation and communication overhead.     

A GIS-based borehole data management and 3D visualization system

The use of subsurface data for problem solving is limited in part by the freedom the user has in their choice of data structures. If a user is allowed to work with the data in a familiar way, they can spend more time performing analysis tasks and less time restructuring data, thus increasing productivity and reducing the risks associated with a series of data modification cycles. Borehole information system (BoreIS) is based upon this principle. Design was guided by interviews with geologists who were targeted as potential users of the software, and BoreIS was developed as an extension to ESRI's ArcScene three-dimensional (3D) GIS environment. BoreIS uses borehole or well data supplied by the user to develop a 3D GIS representation which can be queried, visualized, and analysed. By asking relevant questions about data stored in Excel spreadsheets, BoreIS can automate many high-level GIS functions so that an inexperienced GIS user can still use the system. By matching table elements to spatially and geologically significant terms through the interactive setup, users can work with the data more closely matched to the geological problem domain. This allows the novice user to use powerful GIS functions to discover spatial patterns in their data. BoreIS’ interactive manipulation of terms in complex queries, simple addition of contoured surfaces, and masking by lithology or formation helps geologists find spatial patterns in their data, beyond the limits of data tables and flat maps.     

Towards a graph-based user profile modeling for a session-based personalized search

Most Web search engines use the content of the Web documents and their link structures to assess the relevance of the document to the user’s query. With the growth of the information available on the web, it becomes difficult for such Web search engines to satisfy the user information need expressed by few keywords. First, personalized information retrieval is a promising way to resolve this problem by modeling the user profile by his general interests and then integrating it in a personalized document ranking model. In this paper, we present a personalized search approach that involves a graph-based representation of the user profile. The user profile refers to the user interest in a specific search session defined as a sequence of related queries. It is built by means of score propagation that allows activating a set of semantically related concepts of reference ontology, namely the ODP. The user profile is maintained across related search activities using a graph-based merging strategy. For the purpose of detecting related search activities, we define a session boundary recognition mechanism based on the Kendall rank correlation measure that tracks changes in the dominant concepts held by the user profile relatively to a new submitted query. Personalization is performed by re-ranking the search results of related queries using the user profile. Our experimental evaluation is carried out using the HARD 2003 TREC collection and showed that our session boundary recognition mechanism based on the Kendall measure provides a significant precision comparatively to other non-ranking based measures like the cosine and the WebJaccard similarity measures. Moreover, results proved that the graph-based search personalization is effective for improving the search accuracy.