The Experts below are selected from a list of 29328 Experts worldwide ranked by ideXlab platform
Xuemin Lin - One of the best experts on this subject based on the ideXlab platform.
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inverted linear quadtree efficient top k spatial Keyword Search
IEEE Transactions on Knowledge and Data Engineering, 2016Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study two fundamental problems in the spatial Keyword queries: top $k$ spatial Keyword Search (TOPK-SK), and batch top $k$ spatial Keyword Search (BTOPK-SK). Given a set of spatio-textual objects, a query location and a set of query Keywords, the TOPK-SK retrieves the closest $k$ objects each of which contains all Keywords in the query. BTOPK-SK is the batch processing of sets of TOPK-SK queries. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top $k$ spatial Keyword Search. To further enhance the filtering capability of the signature of linear quadtree, we propose a partition based method. In addition, to deal with BTOPK-SK, we design a new computing paradigm which partition the queries into groups based on both spatial proximity and the textual relevance between queries. We show that the IL-Quadtree technique can also efficiently support BTOPK-SK. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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diversified spatial Keyword Search on road networks
Extending Database Technology, 2014Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Xiaoyang WangAbstract:With the increasing pervasiveness of the geo-positioning technologies, there is an enormous amount of spatio-textual objects available in many applications such as location based services and social networks. Consequently, various types of spatial Keyword Searches which explore both locations and textual descriptions of the objects have been intensively studied by the reSearch communities and commercial organizations. In many important applications (e.g., location based services), the closeness of two spatial objects is measured by the road network distance. Moreover, the result diversification is becoming a common practice to enhance the quality of the Search results. Motived by the above facts, in this paper we study the problem of diversified spatial Keyword Search on road networks which considers both the relevance and the spatial diversity of the results. An efficient signature-based inverted indexing technique is proposed to facilitate the spatial Keyword query processing on road networks. Then we develop an efficient diversified spatial Keyword Search algorithm by taking advantage of spatial Keyword pruning and diversity pruning techniques. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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inverted linear quadtree efficient top k spatial Keyword Search
International Conference on Data Engineering, 2013Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study the problem of top k spatial Keyword Search (TOPK-SK), which is fundamental in the spatial Keyword queries. Given a set of spatio-textual objects, a query location and a set of query Keywords, the top k spatial Keyword Search retrieves the closest k objects each of which contains all Keywords in the query. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top k spatial Keyword Search. In addition, we show that the IL-Quadtree technique can also be applied to improve the performance of other spatial Keyword queries such as the direction-aware top k spatial Keyword Search and the spatio-textual ranking query. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
Chengyuan Zhang - One of the best experts on this subject based on the ideXlab platform.
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inverted linear quadtree efficient top k spatial Keyword Search
IEEE Transactions on Knowledge and Data Engineering, 2016Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study two fundamental problems in the spatial Keyword queries: top $k$ spatial Keyword Search (TOPK-SK), and batch top $k$ spatial Keyword Search (BTOPK-SK). Given a set of spatio-textual objects, a query location and a set of query Keywords, the TOPK-SK retrieves the closest $k$ objects each of which contains all Keywords in the query. BTOPK-SK is the batch processing of sets of TOPK-SK queries. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top $k$ spatial Keyword Search. To further enhance the filtering capability of the signature of linear quadtree, we propose a partition based method. In addition, to deal with BTOPK-SK, we design a new computing paradigm which partition the queries into groups based on both spatial proximity and the textual relevance between queries. We show that the IL-Quadtree technique can also efficiently support BTOPK-SK. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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diversified spatial Keyword Search on road networks
Extending Database Technology, 2014Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Xiaoyang WangAbstract:With the increasing pervasiveness of the geo-positioning technologies, there is an enormous amount of spatio-textual objects available in many applications such as location based services and social networks. Consequently, various types of spatial Keyword Searches which explore both locations and textual descriptions of the objects have been intensively studied by the reSearch communities and commercial organizations. In many important applications (e.g., location based services), the closeness of two spatial objects is measured by the road network distance. Moreover, the result diversification is becoming a common practice to enhance the quality of the Search results. Motived by the above facts, in this paper we study the problem of diversified spatial Keyword Search on road networks which considers both the relevance and the spatial diversity of the results. An efficient signature-based inverted indexing technique is proposed to facilitate the spatial Keyword query processing on road networks. Then we develop an efficient diversified spatial Keyword Search algorithm by taking advantage of spatial Keyword pruning and diversity pruning techniques. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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inverted linear quadtree efficient top k spatial Keyword Search
International Conference on Data Engineering, 2013Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study the problem of top k spatial Keyword Search (TOPK-SK), which is fundamental in the spatial Keyword queries. Given a set of spatio-textual objects, a query location and a set of query Keywords, the top k spatial Keyword Search retrieves the closest k objects each of which contains all Keywords in the query. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top k spatial Keyword Search. In addition, we show that the IL-Quadtree technique can also be applied to improve the performance of other spatial Keyword queries such as the direction-aware top k spatial Keyword Search and the spatio-textual ranking query. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
Ying Zhang - One of the best experts on this subject based on the ideXlab platform.
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inverted linear quadtree efficient top k spatial Keyword Search
IEEE Transactions on Knowledge and Data Engineering, 2016Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study two fundamental problems in the spatial Keyword queries: top $k$ spatial Keyword Search (TOPK-SK), and batch top $k$ spatial Keyword Search (BTOPK-SK). Given a set of spatio-textual objects, a query location and a set of query Keywords, the TOPK-SK retrieves the closest $k$ objects each of which contains all Keywords in the query. BTOPK-SK is the batch processing of sets of TOPK-SK queries. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top $k$ spatial Keyword Search. To further enhance the filtering capability of the signature of linear quadtree, we propose a partition based method. In addition, to deal with BTOPK-SK, we design a new computing paradigm which partition the queries into groups based on both spatial proximity and the textual relevance between queries. We show that the IL-Quadtree technique can also efficiently support BTOPK-SK. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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diversified spatial Keyword Search on road networks
Extending Database Technology, 2014Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Xiaoyang WangAbstract:With the increasing pervasiveness of the geo-positioning technologies, there is an enormous amount of spatio-textual objects available in many applications such as location based services and social networks. Consequently, various types of spatial Keyword Searches which explore both locations and textual descriptions of the objects have been intensively studied by the reSearch communities and commercial organizations. In many important applications (e.g., location based services), the closeness of two spatial objects is measured by the road network distance. Moreover, the result diversification is becoming a common practice to enhance the quality of the Search results. Motived by the above facts, in this paper we study the problem of diversified spatial Keyword Search on road networks which considers both the relevance and the spatial diversity of the results. An efficient signature-based inverted indexing technique is proposed to facilitate the spatial Keyword query processing on road networks. Then we develop an efficient diversified spatial Keyword Search algorithm by taking advantage of spatial Keyword pruning and diversity pruning techniques. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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inverted linear quadtree efficient top k spatial Keyword Search
International Conference on Data Engineering, 2013Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study the problem of top k spatial Keyword Search (TOPK-SK), which is fundamental in the spatial Keyword queries. Given a set of spatio-textual objects, a query location and a set of query Keywords, the top k spatial Keyword Search retrieves the closest k objects each of which contains all Keywords in the query. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top k spatial Keyword Search. In addition, we show that the IL-Quadtree technique can also be applied to improve the performance of other spatial Keyword queries such as the direction-aware top k spatial Keyword Search and the spatio-textual ranking query. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
Wenjie Zhang - One of the best experts on this subject based on the ideXlab platform.
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inverted linear quadtree efficient top k spatial Keyword Search
IEEE Transactions on Knowledge and Data Engineering, 2016Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study two fundamental problems in the spatial Keyword queries: top $k$ spatial Keyword Search (TOPK-SK), and batch top $k$ spatial Keyword Search (BTOPK-SK). Given a set of spatio-textual objects, a query location and a set of query Keywords, the TOPK-SK retrieves the closest $k$ objects each of which contains all Keywords in the query. BTOPK-SK is the batch processing of sets of TOPK-SK queries. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top $k$ spatial Keyword Search. To further enhance the filtering capability of the signature of linear quadtree, we propose a partition based method. In addition, to deal with BTOPK-SK, we design a new computing paradigm which partition the queries into groups based on both spatial proximity and the textual relevance between queries. We show that the IL-Quadtree technique can also efficiently support BTOPK-SK. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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diversified spatial Keyword Search on road networks
Extending Database Technology, 2014Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Xiaoyang WangAbstract:With the increasing pervasiveness of the geo-positioning technologies, there is an enormous amount of spatio-textual objects available in many applications such as location based services and social networks. Consequently, various types of spatial Keyword Searches which explore both locations and textual descriptions of the objects have been intensively studied by the reSearch communities and commercial organizations. In many important applications (e.g., location based services), the closeness of two spatial objects is measured by the road network distance. Moreover, the result diversification is becoming a common practice to enhance the quality of the Search results. Motived by the above facts, in this paper we study the problem of diversified spatial Keyword Search on road networks which considers both the relevance and the spatial diversity of the results. An efficient signature-based inverted indexing technique is proposed to facilitate the spatial Keyword query processing on road networks. Then we develop an efficient diversified spatial Keyword Search algorithm by taking advantage of spatial Keyword pruning and diversity pruning techniques. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
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inverted linear quadtree efficient top k spatial Keyword Search
International Conference on Data Engineering, 2013Co-Authors: Chengyuan Zhang, Ying Zhang, Wenjie Zhang, Xuemin LinAbstract:With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of Keywords (terms). Consequently, the study of spatial Keyword Search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and reSearch communities. In the paper, we study the problem of top k spatial Keyword Search (TOPK-SK), which is fundamental in the spatial Keyword queries. Given a set of spatio-textual objects, a query location and a set of query Keywords, the top k spatial Keyword Search retrieves the closest k objects each of which contains all Keywords in the query. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and Keyword based pruning techniques to effectively reduce the Search space. An efficient algorithm is then developed to tackle top k spatial Keyword Search. In addition, we show that the IL-Quadtree technique can also be applied to improve the performance of other spatial Keyword queries such as the direction-aware top k spatial Keyword Search and the spatio-textual ranking query. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.
Dong Hoon Lee - One of the best experts on this subject based on the ideXlab platform.
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on a security model of conjunctive Keyword Search over encrypted relational database
Journal of Systems and Software, 2011Co-Authors: Jin Wook Byun, Dong Hoon LeeAbstract:Abstract: We study a security model for Searching documents containing each of several Keywords (conjunctive Keyword Search) over encrypted documents. A conjunctive Keyword Search protocol consists of three entities: a data supplier, a storage system such as database, and a user of storage system. A data supplier uploads encrypted documents on a storage system, and then a user of the storage system Searches documents containing each of several Keywords with a private trapdoor. That is, a valid user is able to use boolean combinations of queries. Up to now only few conjunctive Keyword Search schemes have been proposed in the literature. However, the relying security model has not been based on relational databases such as Oracle and MS-Access, hence it is not easy to apply them in practice. Moreover, they have not considered an important security notion for user's trapdoor queries. In this paper, we first formally define a security model for conjunctive Keyword Search schemes including trapdoor security based on a practical relational database. We apply our security model to the existing conjunctive Keyword scheme and discuss its vulnerability and countermeasure.
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difference set attacks on conjunctive Keyword Search schemes
SIAM International Conference on Data Mining, 2006Co-Authors: Hyun Sook Rhee, Ik Rae Jeong, Jin Wook Byun, Dong Hoon LeeAbstract:In a Keyword Search scheme a user stores encrypted data on an untrusted server and gives a database manager a capability for a Keyword which enables a database manager to find encrypted data containing the Keyword without revealing the Keyword to the database manager. Conjunctive Keyword Search scheme enables a user to obtain data containing all of several Keywords through only one query. One of the security requirements of conjunctive Keyword Search schemes is that a malicious adversary should not be able to generate new valid capabilities from the observed capabilities. In this paper we show that conjunctive Keyword Search schemes are not secure. In particular, given two capabilities corresponding two sets of Keywords, an adversary is able to generate a new capability corresponding to the difference set of two Keywords sets.
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off line Keyword guessing attacks on recent Keyword Search schemes over encrypted data
SIAM International Conference on Data Mining, 2006Co-Authors: Jin Wook Byun, Hyun Suk Rhee, Hyuna Park, Dong Hoon LeeAbstract:A Keyword Search scheme over encrypted documents allows for remote Keyword Search of documents by a user in possession of a trapdoor (secret key). A data supplier first uploads encrypted documents on a storage system, and then a user of the storage system Searches documents containing Keywords while insider (such as administrators of the storage system) and outsider attackers do not learn anything else about the documents. In this paper, we firstly raise a serious vulnerability of recent Keyword Search schemes, which lies in the fact that Keywords are chosen from much smaller space than passwords and users usually use well-known Keywords for Search of document. Hence this fact sufficiently gives rise to an off-line Keyword guessing attack. Unfortunately, we observe that the recent public key-based Keyword Search schemes are susceptible to an off-line Keyword guessing attack. We demonstrated that anyone (insider/outsider) can retrieve information of certain Keyword from any captured query messages.
