SemTagP: Semantic Community Detection in Folksonomies

Abstract : Building on top of our results on semantic social network analysis, we present a community detection algorithm, SemTagP, that takes benefits of the semantic data that were captured while structuring the RDF graphs of social networks. SemTagP not only offers to detect but also to label communities by exploiting (in addition to the structure of the social graph) the tags used by people during the social tagging process as well as the semantic relations inferred between tags. Doing so, we are able to refine the partitioning of the social graph with semantic processing and to label the activity of detected communities. We tested and evaluated this algorithm on the social network built from Ph.D. theses funded by ADEME, the French Environment and Energy Management Agency. We showed how this approach allows us to detect and label communities of interest and control the precision of the labels.
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Communication dans un congrès
2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Aug 2011, Lyon, France. 2011, <http://liris.cnrs.fr/~wi-iat11/WI_2011/>. <10.1109/WI-IAT.2011.98>


https://hal.inria.fr/hal-01170978
Contributeur : Fabien Gandon <>
Soumis le : jeudi 2 juillet 2015 - 16:06:22
Dernière modification le : mercredi 14 décembre 2016 - 01:07:05

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Guillaume Erétéo, Fabien Gandon, Michel Buffa. SemTagP: Semantic Community Detection in Folksonomies. 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Aug 2011, Lyon, France. 2011, <http://liris.cnrs.fr/~wi-iat11/WI_2011/>. <10.1109/WI-IAT.2011.98>. <hal-01170978>

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