An algorithm for min-cut density-balanced partitioning in P2P web ranking
© Springer International Publishing Switzerland 2015. In P2P-based PageRank computing, each computational peer contains a partitioned local web-link graph and its PageRank is computed locally. Then, collaborative web ranking between any two peers will be proceeded iteratively to adjust the web ranki...
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th-cmuir.6653943832-444362018-04-25T07:50:17Z An algorithm for min-cut density-balanced partitioning in P2P web ranking Sumalee Sangamuang Pruet Boonma Juggapong Natwichai Agricultural and Biological Sciences © Springer International Publishing Switzerland 2015. In P2P-based PageRank computing, each computational peer contains a partitioned local web-link graph and its PageRank is computed locally. Then, collaborative web ranking between any two peers will be proceeded iteratively to adjust the web ranking until converge. In this paper, the problem of partitioning web-link graph for web ranking in P2P is formulated as a minimal cut-set with density-balanced partitioning. Then, an efficient algorithm called DBP-dRanking is proposed to address such problem. The algorithm can solve the problem with computational complexity of a polynomial function to the web-link graph size. The results also confirm that the proposed algorithm can reduce the ranking error by partitioning web-link graph and perform faster than two other algorithms. 2018-01-24T04:42:51Z 2018-01-24T04:42:51Z 2015-01-01 Book Series 21945357 2-s2.0-84931273886 10.1007/978-3-319-19024-2_26 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931273886&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/44436 |
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Agricultural and Biological Sciences Sumalee Sangamuang Pruet Boonma Juggapong Natwichai An algorithm for min-cut density-balanced partitioning in P2P web ranking |
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© Springer International Publishing Switzerland 2015. In P2P-based PageRank computing, each computational peer contains a partitioned local web-link graph and its PageRank is computed locally. Then, collaborative web ranking between any two peers will be proceeded iteratively to adjust the web ranking until converge. In this paper, the problem of partitioning web-link graph for web ranking in P2P is formulated as a minimal cut-set with density-balanced partitioning. Then, an efficient algorithm called DBP-dRanking is proposed to address such problem. The algorithm can solve the problem with computational complexity of a polynomial function to the web-link graph size. The results also confirm that the proposed algorithm can reduce the ranking error by partitioning web-link graph and perform faster than two other algorithms. |
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Book Series |
author |
Sumalee Sangamuang Pruet Boonma Juggapong Natwichai |
author_facet |
Sumalee Sangamuang Pruet Boonma Juggapong Natwichai |
author_sort |
Sumalee Sangamuang |
title |
An algorithm for min-cut density-balanced partitioning in P2P web ranking |
title_short |
An algorithm for min-cut density-balanced partitioning in P2P web ranking |
title_full |
An algorithm for min-cut density-balanced partitioning in P2P web ranking |
title_fullStr |
An algorithm for min-cut density-balanced partitioning in P2P web ranking |
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An algorithm for min-cut density-balanced partitioning in P2P web ranking |
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algorithm for min-cut density-balanced partitioning in p2p web ranking |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84931273886&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/44436 |
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