完整後設資料紀錄
DC 欄位語言
dc.contributor.authorShen, Chih-Yaen_US
dc.contributor.authorHuang, Liang-Haoen_US
dc.contributor.authorYang, De-Nianen_US
dc.contributor.authorShuai, Hong-Hanen_US
dc.contributor.authorLee, Wang-Chienen_US
dc.contributor.authorChen, Ming-Syanen_US
dc.date.accessioned2019-04-02T06:04:15Z-
dc.date.available2019-04-02T06:04:15Z-
dc.date.issued2017-01-01en_US
dc.identifier.urihttp://dx.doi.org/10.1145/3097983.3097995en_US
dc.identifier.urihttp://hdl.handle.net/11536/150985-
dc.description.abstractExisting research on finding social groups mostly focuses on dense subgraphs in social networks. However, finding socially tenuous groups also has many important applications. In this paper, we introduce the notion of k-triangles to measure the tenuity of a group. We then formulate a new research problem, Minimum k-Triangle Disconnected Group (MkTG), to find a socially tenuous group from online social networks. We prove that MkTG is NP-Hard and inapproximable within any ratio in arbitrary graphs but polynomial-time tractable in threshold graphs. Two algorithms, namely TERA and TERA-ADV, are designed to exploit graph theoretical approaches for solving MkTG on general graphs effectively and efficiently. Experimental results on seven real datasets manifest that the proposed algorithms outperform existing approaches in both efficiency and solution quality.en_US
dc.language.isoen_USen_US
dc.titleOn Finding Socially Tenuous Groups for Online Social Networksen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1145/3097983.3097995en_US
dc.identifier.journalKDD'17: PROCEEDINGS OF THE 23RD ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MININGen_US
dc.citation.spage415en_US
dc.citation.epage424en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000455787300056en_US
dc.citation.woscount1en_US
顯示於類別:會議論文