Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김상욱 | - |
dc.date.accessioned | 2022-06-09T05:56:39Z | - |
dc.date.available | 2022-06-09T05:56:39Z | - |
dc.date.issued | 2020-10 | - |
dc.identifier.citation | Proceedings of the 29th ACM International Conference on Information & Knowledge Management, page. 2077-2080 | en_US |
dc.identifier.isbn | 978-1-4503-6859-9 | - |
dc.identifier.uri | https://dl.acm.org/doi/abs/10.1145/3340531.3412145? | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/171309 | - |
dc.description.abstract | In this paper, we present CR-Graph (community reinforcement on graphs), a novel method that helps existing algorithms to perform more-accurate community detection (CD). Toward this end, CRGraph strengthens the community structure of a given original graph by adding non-existent predicted intra-community edges and deleting existing predicted inter-community edges. To design CRGraph, we propose the following two strategies: (1) predicting intracommunity and inter-community edges (i.e., the type of edges) and (2) determining the amount of edges to be added/deleted. To show the effectiveness of CR-Graph, we conduct extensive experiments with various CD algorithms on 7 synthetic and 4 real-world graphs. The results demonstrate that CR-Graph improves the accuracy of all underlying CD algorithms universally and consistently. | en_US |
dc.description.sponsorship | This research was supported by (1) the National Research Foundation of Korea grant funded by the Korea government (NRF2020R1A2B5B03001960), (2) the National Research Foundation of Korea grant funded by the Korea government (2018R1A5A7059549), and (3) the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT (NRF-2017M3C4A7069440). | en_US |
dc.language.iso | en | en_US |
dc.publisher | ACM CIKM 2020 | en_US |
dc.subject | community detection | en_US |
dc.subject | community reinforcement | en_US |
dc.subject | inter-community edges | en_US |
dc.subject | intra-community edges | en_US |
dc.subject | preprocessing | en_US |
dc.title | CR-Graph: Community Reinforcement on Graphs for Accurate Community Detection | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1145/3340531.3412145 | - |
dc.relation.page | 2077-2080 | - |
dc.contributor.googleauthor | Kang, Yoonsuk | - |
dc.contributor.googleauthor | Lee, Jun Seok | - |
dc.contributor.googleauthor | Shin, Won-Yong | - |
dc.contributor.googleauthor | Kim, Sang-Wook | - |
dc.relation.code | 20200042 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | SCHOOL OF COMPUTER SCIENCE | - |
dc.identifier.pid | wook | - |
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