Efficient algorithms for generalized subgraph query processing
We study a new type of graph queries, which injectively maps its edges to paths of the graphs in a given database, where the length of each path is constrained by a given threshold specified by the weight of the corresponding matching edge. We give important applications of the new graph query and i...
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sg-ntu-dr.10356-979632020-05-28T07:17:35Z Efficient algorithms for generalized subgraph query processing Bhowmick, Sourav S. Cheng, James Lin, Wenqing Xiao, Xiaokui School of Computer Engineering International conference on Information and knowledge management (21st : 2012 : Maui, USA) DRNTU::Engineering::Computer science and engineering We study a new type of graph queries, which injectively maps its edges to paths of the graphs in a given database, where the length of each path is constrained by a given threshold specified by the weight of the corresponding matching edge. We give important applications of the new graph query and identify new challenges of processing such a query. Then, we devise the cost model of the branch-and-bound algorithm framework for processing the graph query, and propose an efficient algorithm to minimize the cost overhead. We also develop three indexing techniques to efficiently answer the queries online. Finally, we verify the efficiency of our proposed indexes with extensive experiments on large real and synthetic datasets. 2013-07-25T08:08:36Z 2019-12-06T19:48:51Z 2013-07-25T08:08:36Z 2019-12-06T19:48:51Z 2012 2012 Conference Paper Lin, W., Xiao, X., Cheng, J., & Bhowmick, S. S. (2012). Efficient algorithms for generalized subgraph query processing. Proceedings of the 21st ACM international conference on Information and knowledge management. https://hdl.handle.net/10356/97963 http://hdl.handle.net/10220/12302 10.1145/2396761.2396805 en © 2012 ACM. |
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DRNTU::Engineering::Computer science and engineering Bhowmick, Sourav S. Cheng, James Lin, Wenqing Xiao, Xiaokui Efficient algorithms for generalized subgraph query processing |
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We study a new type of graph queries, which injectively maps its edges to paths of the graphs in a given database, where the length of each path is constrained by a given threshold specified by the weight of the corresponding matching edge. We give important applications of the new graph query and identify new challenges of processing such a query. Then, we devise the cost model of the branch-and-bound algorithm framework for processing the graph query, and propose an efficient algorithm to minimize the cost overhead. We also develop three indexing techniques to efficiently answer the queries online. Finally, we verify the efficiency of our proposed indexes with extensive experiments on large real and synthetic datasets. |
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School of Computer Engineering |
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School of Computer Engineering Bhowmick, Sourav S. Cheng, James Lin, Wenqing Xiao, Xiaokui |
format |
Conference or Workshop Item |
author |
Bhowmick, Sourav S. Cheng, James Lin, Wenqing Xiao, Xiaokui |
author_sort |
Bhowmick, Sourav S. |
title |
Efficient algorithms for generalized subgraph query processing |
title_short |
Efficient algorithms for generalized subgraph query processing |
title_full |
Efficient algorithms for generalized subgraph query processing |
title_fullStr |
Efficient algorithms for generalized subgraph query processing |
title_full_unstemmed |
Efficient algorithms for generalized subgraph query processing |
title_sort |
efficient algorithms for generalized subgraph query processing |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/97963 http://hdl.handle.net/10220/12302 |
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