research-article

Fast top-k similarity join for SimRank

Information Sciences—Informatics and Computer Science, Intelligent Systems, Applications: An International Journal, Volume 381, Issue C

Pages 1 - 19

https://doi.org/10.1016/j.ins.2016.10.042

Published: 01 March 2017 Publication History

Abstract

SimRank is a well-studied similarity measure between two nodes in a network. However, evaluating SimRank of all nodes in a network is not only time-consuming but also not pragmatic, since users are only interested in the most similar pairs in many real-world applications. This paper focuses on top-k similarity join based on SimRank. In this work, we first present an incremental algorithm for computing SimRank. On top of that, we derive an iterative batch pruning framework, which is able to iteratively filter out unpromising nodes and obtain the top-k pairs in a fast mode. Specifically, we define the concept of super node such that for a node in the network, the SimRank with its super node is not less than that with any others. Based on this feature, we propose a tight upper bound for each node that can be easily calculated after each iteration. Experiments on both real-life and synthetic datasets demonstrate that our method achieves better performance and scalability, in comparison with the state-of-the-art solution.

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Cited By

Ge QLiu YZhao YSun YZou LChen YPan A(2023)Efficient and Accurate SimRank-Based Similarity Joins: Experiments, Analysis, and ImprovementProceedings of the VLDB Endowment10.14778/3636218.363621917:4(617-629)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.14778/3636218.3636219
Zhang MXiao YWang WSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Efficient Single-Source SimRank Query by Path AggregationProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599328(3342-3352)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599328
Lin PLi YLuo WZhou XZeng YLi KLi K(2022)Personalized query techniques in graphsInformation Sciences: an International Journal10.1016/j.ins.2022.06.023607:C(961-1000)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1016/j.ins.2022.06.023
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Fast top-k similarity join for SimRank
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cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 381, Issue C

March 2017

371 pages

ISSN:0020-0255

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Copyright © Elsevier Inc.

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Elsevier Science Inc.

United States

Publication History

Published: 01 March 2017

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Cited By

Ge QLiu YZhao YSun YZou LChen YPan A(2023)Efficient and Accurate SimRank-Based Similarity Joins: Experiments, Analysis, and ImprovementProceedings of the VLDB Endowment10.14778/3636218.363621917:4(617-629)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.14778/3636218.3636219
Zhang MXiao YWang WSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Efficient Single-Source SimRank Query by Path AggregationProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599328(3342-3352)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599328
Lin PLi YLuo WZhou XZeng YLi KLi K(2022)Personalized query techniques in graphsInformation Sciences: an International Journal10.1016/j.ins.2022.06.023607:C(961-1000)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1016/j.ins.2022.06.023
Ding XYang WRaymond Choo KWang XJin H(2022)Privacy preserving similarity joins using MapReduceInformation Sciences: an International Journal10.1016/j.ins.2019.03.035493:C(20-33)Online publication date: 20-Apr-2022
https://dl.acm.org/doi/10.1016/j.ins.2019.03.035
Zhao SCao X(2020)Multiple-user closest keyword-set querying in road networksInformation Sciences: an International Journal10.1016/j.ins.2019.09.009509:C(133-149)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1016/j.ins.2019.09.009
Wang JZhang MHe ZWang WSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Partial sums-based P-Rank computation in information networksProceedings of the International Conference on Web Intelligence10.1145/3106426.3109447(1122-1130)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3109447

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