Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies

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dc.contributor.authorJava, Akshay
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-21T19:47:11Z
dc.date.available2018-11-21T19:47:11Z
dc.date.issued2008-08-24
dc.descriptionProceedings of the Tenth Workshop on Web Mining and Web Usage Analysis (WebKDD)en_US
dc.description.abstractWe present a simple technique for detecting communities by utilizing both the link structure and folksonomy (or tag) information that is readily available in most social media systems. A simple way to describe our approach is by defining a community as a set of nodes in a graph that link more frequently to within this set than outside it and they share similar tags. Our technique is based on the Normalized Cut (NCut) algorithm and can be easily and efficiently implemented. We validate our method by using a real network of blogs and tag information obtained from a social bookmarking site. We also verify our results on a citation network for which we have access to ground truth cluster information. Our method, Simultaneous Cut (SimCut), has the advantage that it can group related tags and cluster the nodes simultaneously.en_US
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/406/Detecting-Commmunities-via-Simultaneous-Clustering-of-Graphs-and-Folksonomiesen_US
dc.format.extent14 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M2X34MW6K
dc.identifier.citationAkshay Java, Anupam Joshi, and Tim Finin, Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies, Proceedings of the Tenth Workshop on Web Mining and Web Usage Analysis (WebKDD), 2008, https://ebiquity.umbc.edu/paper/html/id/406/Detecting-Commmunities-via-Simultaneous-Clustering-of-Graphs-and-Folksonomiesen_US
dc.identifier.urihttp://hdl.handle.net/11603/12078
dc.language.isoen_USen_US
dc.publisherACMen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectDetecting Commmunitiesen_US
dc.subjectSimultaneous Clusteringen_US
dc.subjectGraphsen_US
dc.subjectFolksonomiesen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleDetecting Commmunities via Simultaneous Clustering of Graphs and Folksonomiesen_US
dc.typeTexten_US

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