Fast Algorithm for Attributed Community Search
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- Matsugu Shohei
- University of Tsukuba
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- Shiokawa Hiroaki
- University of Tsukuba
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- Kitagawa Hiroyuki
- University of Tsukuba
Abstract
<p>Searching communities on attributed graphs has attracted much attention in recent years. The community search algorithm is currently an essential graph data management tool to find a community suited to a user-specified query node. Although community search algorithms are useful in various web-based applications and services, they have trouble handling attributed graphs due to the strict topological constraints of traditional algorithms. In this paper, we propose an accurate community search algorithm for attributed graphs. To relax the topological constraints, we proposed a new model of the community. And we defined the problem of finding them in an attributed graph class called the Flexible Attributed Truss Community (F-ATC). The F-ATC problem has the advantage of being applicable in many situations because it can explore diverse communities. Consequently, the community search accuracy is enhanced compared to traditional community search algorithms. Additionally, we present a novel heuristic algorithm to solve the F-ATC problem. This effective algorithm detects more accurate communities from attributed graphs than the traditional algorithms. For further optimization, we pre-processed the query response to make it faster. Finally, we conducted extensive experiments with real-world attributed graphs to demonstrate that our approach outperforms state-of-the-art methods.</p>
Journal
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- Journal of Information Processing
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Journal of Information Processing 29 (0), 188-196, 2021
Information Processing Society of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390850092196640000
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- NII Article ID
- 130007986878
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- ISSN
- 18826652
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed