Searching Substructures with Superimposed Distance
Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved yet. In this paper, we develop a method called PIS (...
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2006
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sg-smu-ink.sis_research-19382017-11-22T07:56:23Z Searching Substructures with Superimposed Distance YAN, Xifeng ZHU, Feida HAN, Jiawei YU, Philip S. Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved yet. In this paper, we develop a method called PIS (Partition-based Graph Index and Search) to support similarity search on substructures with superimposed distance constraints. PIS selects discriminative fragments in a query graph and uses an index to prune the graphs that violate the distance constraints. We identify a criterion to distinguish the selectivity of fragments in multiple graphs and develop a partition method to obtain a set of highly selective fragments, which is able to improve the pruning performance. Experimental results show that PIS is effective in processing real graph queries. 2006-04-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/939 info:doi/10.1109/ICDE.2006.136 https://ink.library.smu.edu.sg/context/sis_research/article/1938/viewcontent/SearchingSubstructures_2006.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Numerical Analysis and Scientific Computing |
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Databases and Information Systems Numerical Analysis and Scientific Computing YAN, Xifeng ZHU, Feida HAN, Jiawei YU, Philip S. Searching Substructures with Superimposed Distance |
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Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved yet. In this paper, we develop a method called PIS (Partition-based Graph Index and Search) to support similarity search on substructures with superimposed distance constraints. PIS selects discriminative fragments in a query graph and uses an index to prune the graphs that violate the distance constraints. We identify a criterion to distinguish the selectivity of fragments in multiple graphs and develop a partition method to obtain a set of highly selective fragments, which is able to improve the pruning performance. Experimental results show that PIS is effective in processing real graph queries. |
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YAN, Xifeng ZHU, Feida HAN, Jiawei YU, Philip S. |
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YAN, Xifeng ZHU, Feida HAN, Jiawei YU, Philip S. |
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YAN, Xifeng |
title |
Searching Substructures with Superimposed Distance |
title_short |
Searching Substructures with Superimposed Distance |
title_full |
Searching Substructures with Superimposed Distance |
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Searching Substructures with Superimposed Distance |
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Searching Substructures with Superimposed Distance |
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searching substructures with superimposed distance |
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Institutional Knowledge at Singapore Management University |
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2006 |
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https://ink.library.smu.edu.sg/sis_research/939 https://ink.library.smu.edu.sg/context/sis_research/article/1938/viewcontent/SearchingSubstructures_2006.pdf |
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