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題名 Regional subgraph discovery in social networks
作者 Li, C.-T.;Shan, Man-Kwan;Lin, Shou-De
沈錳坤;林守德
貢獻者 資科系
關鍵詞 Coauthorship; Edge weights; High precision; Information backbone; Query nodes; Region-based; Regional networks; Similar Interests; Social Networks; Subgraphs; Viral marketing; Social networking (online); World Wide Web; Graph theory
日期 2012
上傳時間 17-Apr-2015 10:55:43 (UTC+8)
摘要 This paper solves a region-based subgraph discovery problem. We are given a social network and some sample nodes which is supposed to belong to a specific region, and the goal is to obtain a subgraph that contains the sampled nodes with other nodes in the same region. Such regional subgraph discovery can benefit regionbased applications, including scholar search, friend suggestion, and viral marketing. To deal with this problem, we assume there is a hidden backbone connecting the query nodes directly or indirectly in their region. The idea is that individuals belonging to the same region tend to share similar interests and cultures. By modeling such fact on edge weights, we search the graph to extract the regional backbone with respect to the query nodes. Then we can expand the backbone to derive the regional network. Experiments on a DBLP co-authorship network show the proposed method can effectively discover the regional subgraph with high precision scores. Copyright is held by the author/owner(s).
關聯 WWW`12 - Proceedings of the 21st Annual Conference on World Wide Web Companion
資料類型 conference
DOI http://dx.doi.org/10.1145/2187980.2188128
dc.contributor 資科系
dc.creator (作者) Li, C.-T.;Shan, Man-Kwan;Lin, Shou-De
dc.creator (作者) 沈錳坤;林守德zh_TW
dc.date (日期) 2012
dc.date.accessioned 17-Apr-2015 10:55:43 (UTC+8)-
dc.date.available 17-Apr-2015 10:55:43 (UTC+8)-
dc.date.issued (上傳時間) 17-Apr-2015 10:55:43 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/74651-
dc.description.abstract (摘要) This paper solves a region-based subgraph discovery problem. We are given a social network and some sample nodes which is supposed to belong to a specific region, and the goal is to obtain a subgraph that contains the sampled nodes with other nodes in the same region. Such regional subgraph discovery can benefit regionbased applications, including scholar search, friend suggestion, and viral marketing. To deal with this problem, we assume there is a hidden backbone connecting the query nodes directly or indirectly in their region. The idea is that individuals belonging to the same region tend to share similar interests and cultures. By modeling such fact on edge weights, we search the graph to extract the regional backbone with respect to the query nodes. Then we can expand the backbone to derive the regional network. Experiments on a DBLP co-authorship network show the proposed method can effectively discover the regional subgraph with high precision scores. Copyright is held by the author/owner(s).
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) WWW`12 - Proceedings of the 21st Annual Conference on World Wide Web Companion
dc.subject (關鍵詞) Coauthorship; Edge weights; High precision; Information backbone; Query nodes; Region-based; Regional networks; Similar Interests; Social Networks; Subgraphs; Viral marketing; Social networking (online); World Wide Web; Graph theory
dc.title (題名) Regional subgraph discovery in social networks
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1145/2187980.2188128
dc.doi.uri (DOI) http://dx.doi.org/10.1145/2187980.2188128