The Experts below are selected from a list of 255 Experts worldwide ranked by ideXlab platform
Nicolas Spyratos - One of the best experts on this subject based on the ideXlab platform.
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tiger querying a Relational Table through criteria extension
Soft Computing and Pattern Recognition, 2010Co-Authors: Yoann Pitarch, Dominique Laurent, Pascal Poncelet, Nicolas SpyratosAbstract:Sales on the Internet have increased sig- nificantly during the last decade, and so, it is crucial for companies to retain customers on their web site. Among all strategies towards this goal, providing customers with a flexible search tool is a crucial issue. In this paper, we propose an approach, called TIGER, for handling such flexibility automatically. More precisely, if the search criteria of a given query to a Relational Table or a Web catalog are too restric- tive, our approach computes a new query combining extensions of the criteria. This new query maximizes the quality of the answer, while being as close as possible to the original query. Experiments show that our approach improves the quality of queries, in the sense explained just above.
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Computing Supports of Conjunctive Queries on Relational Tables with Functional Dependencies
Fundamenta Informaticae, 2010Co-Authors: Dominique Laurent, Nicolas SpyratosAbstract:The problem of mining all frequent queries on a Relational Table is a problem known to be intracTable even for conjunctive queries. In this article, we restrict our attention to conjunctive projection-selection queries and we assume that the Table to be mined satisfies a set of functional dependencies. Under these assumptions, we define and characterize two pre-orderings with respect to which the support measure is shown to be anti-monotonic. Each of these pre-orderings induces an equivalence relation for which all queries of the same equivalence class have the same support. The goal of this article is not to provide algorithms for the computation of frequent queries, but rather to provide basic properties of pre-orderings and their associated equivalence relations showing that functional dependencies can be used for an optimized computation of supports of conjunctive queries. In particular, we show that one of the two pre-orderings characterizes anti-monotonicity of the support, while the other one refines the former, but allows to characterize anti-monotonicity with respect to a given Table, only. Basic computational implications of these properties are discussed in the article.
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TIGER: Querying large Tables through criteria extension
2010 International Conference of Soft Computing and Pattern Recognition, 2010Co-Authors: Yoann Pitarch, Dominique Laurent, Pascal Poncelet, Nicolas SpyratosAbstract:Sales on the Internet have increased significantly during the last decade, and so, it is crucial for companies to retain customers on their web site. Among all strategies towards this goal, providing customers with a flexible search tool is a crucial issue. In this paper, we propose an approach, called TIGER, for handling such flexibility automatically. More precisely, if the search criteria of a given query to a Relational Table or a Web catalog are too restrictive, our approach computes a new query combining extensions of the criteria. This new query maximizes the quality of the answer, while being as close as possible to the original query. Experiments show that our approach improves the quality of queries, in the sense explained just above.
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mining all frequent projection selection queries from a Relational Table
Extending Database Technology, 2008Co-Authors: Dominique Laurent, Nicolas SpyratosAbstract:In this paper we study the problem of mining all frequent queries in a given database Table, a problem known to be intracTable even for conjunctive queries. We restrict our attention to projection-selection queries, and we assume that the Table to be mined satisfies a set of functional dependencies. Under these assumptions we define a pre-ordering ≺ over queries and we show the following: (a) the support measure is anti-monotonic (with respect to ≺ ), and (b) if we define q ≺ q' iff q ≺ q' and q' ≺ q then all queries of an equivalence class have the same support. With these results at hand, we further restrict our attention to star schemas of data warehouses. In those schemas, the set of functional dependencies satisfies an important property, namely, the union of keys of all dimension Tables is a key for the fact Table. The main contribution of this paper is the proposal of a level-wise algorithm for mining all frequent projection-selection queries in a data warehouse over a star schema. Moreover, we show that, in the case of a star schema, the complexity in the number of scans of our algorithm is similar to that of the well known Apriori algorithm, i.e., linear with respect to the number of attributes.
Aditya Parameswaran - One of the best experts on this subject based on the ideXlab platform.
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Interactive data exploration with smart drill-down
2016 IEEE 32nd International Conference on Data Engineering (ICDE), 2016Co-Authors: Manas Joglekar, Hector Garcia-molina, Aditya ParameswaranAbstract:We present smart drill-down, an operator for interactively exploring a Relational Table to discover and summarize “interesting” groups of tuples. Each group of tuples is described by a rule. For instance, the rule (a, b, *, 1000) tells us that there are a thousand tuples with value a in the first column and b in the second column (and any value in the third column). Smart drill-down presents an analyst with a list of rules that together describe interesting aspects of the Table. The analyst can tailor the definition of interesting, and can interactively apply smart drill-down on an existing rule to explore that part of the Table. We demonstrate that the underlying optimization problems are NP-HARD, and describe an algorithm for finding the approximately optimal list of rules to display when the user uses a smart drill-down, and a dynamic sampling scheme for efficiently interacting with large Tables. Finally, we perform experiments on real datasets on our experimental prototype to demonstrate the usefulness of smart drill-down and study the performance of our algorithms.
Ken Higuchi - One of the best experts on this subject based on the ideXlab platform.
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An extendible array based implementation of Relational Tables for multi dimensional databases
Lecture Notes in Computer Science, 2020Co-Authors: K. M. Azharul Hasan, Masayuki Kuroda, Naoki Azuma, Tatsuo Tsuji, Ken HiguchiAbstract:A new implementation scheme for Relational Tables in multidimensional databases is proposed and evaluated. The scheme implements a Relational Table by employing a multidimensional array. Using multidimensional arrays provides many advantages, however suffers from some problems. In our scheme, these problems are solved by an efficient scheme of record encoding based on the notion of extendible array. Our scheme exhibits good performance in space and time costs compared with conventional implementation.
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A Parallel Implementation Scheme of Relational Tables Based on Multidimensional Extendible Array
Data Warehousing and Mining, 2020Co-Authors: K. M. Azharul Hasan, Tatsuo Tsuji, Ken HiguchiAbstract:In this article, an efficient parallel implementation scheme of Relational Tables is proposed and evaluated. The scheme implements a Relational Table by employing an extendible multidimensional array. Data allocation is a key performance factor for parallel database systems. This holds especially for data warehousing environments in which huge amounts of data have to be dealt with. In our scheme, an efficient data allocation technique is used, based on the notion of extendible array. The dynamic load balancing is conducted when load on each processor is not uniformly distributed in order to maximize processor utilization.
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DaWaK - An extendible array based implementation of Relational Tables for multi dimensional databases
Data Warehousing and Knowledge Discovery, 2005Co-Authors: K. M. Azharul Hasan, Masayuki Kuroda, Naoki Azuma, Tatsuo Tsuji, Ken HiguchiAbstract:A new implementation scheme for Relational Tables in multidimensional databases is proposed and evaluated. The scheme implements a Relational Table by employing a multidimensional array. Using multidimensional arrays provides many advantages, however suffers from some problems. In our scheme, these problems are solved by an efficient scheme of record encoding based on the notion of extendible array. Our scheme exhibits good performance in space and time costs compared with conventional implementation.
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ICDE Workshops - An Implementation Scheme of Relational Tables
21st International Conference on Data Engineering Workshops (ICDEW'05), 2005Co-Authors: Masayuki Kuroda, K. M. Azharul Hasan, Tatsuo Tsuji, N. Amma, Ken HiguchiAbstract:A new implementation scheme for Relational Tables is proposed, and a prototype system based on the scheme is evaluated. The scheme implements a Relational Table by employing a multidimensional array like in MOLAP systems. Using multidimensional arrays provides many advantages, however uses suffer from some problems. In our scheme, these problems are solved by an efficient scheme of record encoding based on the notion of extendible array. Our scheme exhibits good performance in space and time costs compared with conventional implementation.
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An Implementation Scheme of Relational Tables
21st International Conference on Data Engineering Workshops (ICDEW'05), 2005Co-Authors: Masayuki Kuroda, K. M. Azharul Hasan, Tatsuo Tsuji, N. Amma, Ken HiguchiAbstract:A new implementation scheme for Relational Tables is proposed, and a prototype system based on the scheme is evaluated. The scheme implements a Relational Table by employing a multidimensional array like in MOLAP systems. Using multidimensional arrays provides many advantages, however uses suffer from some problems. In our scheme, these problems are solved by an efficient scheme of record encoding based on the notion of extendible array. Our scheme exhibits good performance in space and time costs compared with conventional implementation.
Byeong-soo Jeong - One of the best experts on this subject based on the ideXlab platform.
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Query Aggregation in Wireless Sensor Networks
2020Co-Authors: Min Meng, Hui Xu, Jie Yang, Byeong-soo JeongAbstract:Wireless sensor networks have been used more and more widely with the developments of related techniques in telecommunication and computer sciences. While sensor nodes in wireless sensor networks have very limited memory spaces and power. In this paper, we propose a new query aggregation method to preprocess the query predicates. The size of the Relational Table can be further reduced using the aggregated query predicates. The reduced Relational Table can be stored on the sensor nodes. This may cause false positive but definitely no false negative. When the required data are sent back to the sink, we can do join operation between the real query predicate and the Relational Table again, and eliminate the redundant data. Keyword: Query aggregation, wireless sensor network
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Query Predicate Preprocessing in Wireless Sensor Networks
2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07), 2007Co-Authors: Min Meng, Hui Xu, Byeong-soo JeongAbstract:With the developments of related techniques in telecommunication and computer sciences, wireless sensor networks have been used more and more widely. While sensor nodes in wireless sensor networks have very limited memory spaces and power. In this paper, we propose a new method to preprocess the query predicates. The size of the Relational Table can be further reduced using the aggregated query predicates. The reduced Relational Table can be stored on the sensor nodes. This may cause false positive but definitely no false negative. When the required data are sent back to the sink, we can do join operation between the real query predicate and the Relational Table again, and eliminate the redundant data.
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MUE - Query Predicate Preprocessing in Wireless Sensor Networks
2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07), 2007Co-Authors: Min Meng, Hui Xu, Byeong-soo JeongAbstract:With the developments of related techniques in telecommunication and computer sciences, wireless sensor networks have been used more and more widely. While sensor nodes in wireless sensor networks have very limited memory spaces and power. In this paper, we propose a new method to preprocess the query predicates. The size of the Relational Table can be further reduced using the aggregated query predicates. The reduced Relational Table can be stored on the sensor nodes. This may cause false positive but definitely no false negative. When the required data are sent back to the sink, we can do join operation between the real query predicate and the Relational Table again, and eliminate the redundant data.
Dominique Laurent - One of the best experts on this subject based on the ideXlab platform.
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tiger querying a Relational Table through criteria extension
Soft Computing and Pattern Recognition, 2010Co-Authors: Yoann Pitarch, Dominique Laurent, Pascal Poncelet, Nicolas SpyratosAbstract:Sales on the Internet have increased sig- nificantly during the last decade, and so, it is crucial for companies to retain customers on their web site. Among all strategies towards this goal, providing customers with a flexible search tool is a crucial issue. In this paper, we propose an approach, called TIGER, for handling such flexibility automatically. More precisely, if the search criteria of a given query to a Relational Table or a Web catalog are too restric- tive, our approach computes a new query combining extensions of the criteria. This new query maximizes the quality of the answer, while being as close as possible to the original query. Experiments show that our approach improves the quality of queries, in the sense explained just above.
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Computing Supports of Conjunctive Queries on Relational Tables with Functional Dependencies
Fundamenta Informaticae, 2010Co-Authors: Dominique Laurent, Nicolas SpyratosAbstract:The problem of mining all frequent queries on a Relational Table is a problem known to be intracTable even for conjunctive queries. In this article, we restrict our attention to conjunctive projection-selection queries and we assume that the Table to be mined satisfies a set of functional dependencies. Under these assumptions, we define and characterize two pre-orderings with respect to which the support measure is shown to be anti-monotonic. Each of these pre-orderings induces an equivalence relation for which all queries of the same equivalence class have the same support. The goal of this article is not to provide algorithms for the computation of frequent queries, but rather to provide basic properties of pre-orderings and their associated equivalence relations showing that functional dependencies can be used for an optimized computation of supports of conjunctive queries. In particular, we show that one of the two pre-orderings characterizes anti-monotonicity of the support, while the other one refines the former, but allows to characterize anti-monotonicity with respect to a given Table, only. Basic computational implications of these properties are discussed in the article.
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TIGER: Querying large Tables through criteria extension
2010 International Conference of Soft Computing and Pattern Recognition, 2010Co-Authors: Yoann Pitarch, Dominique Laurent, Pascal Poncelet, Nicolas SpyratosAbstract:Sales on the Internet have increased significantly during the last decade, and so, it is crucial for companies to retain customers on their web site. Among all strategies towards this goal, providing customers with a flexible search tool is a crucial issue. In this paper, we propose an approach, called TIGER, for handling such flexibility automatically. More precisely, if the search criteria of a given query to a Relational Table or a Web catalog are too restrictive, our approach computes a new query combining extensions of the criteria. This new query maximizes the quality of the answer, while being as close as possible to the original query. Experiments show that our approach improves the quality of queries, in the sense explained just above.
-
mining all frequent projection selection queries from a Relational Table
Extending Database Technology, 2008Co-Authors: Dominique Laurent, Nicolas SpyratosAbstract:In this paper we study the problem of mining all frequent queries in a given database Table, a problem known to be intracTable even for conjunctive queries. We restrict our attention to projection-selection queries, and we assume that the Table to be mined satisfies a set of functional dependencies. Under these assumptions we define a pre-ordering ≺ over queries and we show the following: (a) the support measure is anti-monotonic (with respect to ≺ ), and (b) if we define q ≺ q' iff q ≺ q' and q' ≺ q then all queries of an equivalence class have the same support. With these results at hand, we further restrict our attention to star schemas of data warehouses. In those schemas, the set of functional dependencies satisfies an important property, namely, the union of keys of all dimension Tables is a key for the fact Table. The main contribution of this paper is the proposal of a level-wise algorithm for mining all frequent projection-selection queries in a data warehouse over a star schema. Moreover, we show that, in the case of a star schema, the complexity in the number of scans of our algorithm is similar to that of the well known Apriori algorithm, i.e., linear with respect to the number of attributes.
