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Gaining Insight in Social Networks with Biclustering and Triclustering

P. 162–171.
Gnatyshak D. V., Ignatov D. I., Semenov A., Poelmans J.

We combine bi- and triclustering to analyse data collected from the Russian online social network Vkontakte. Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users' interests as tags and use them to describe Vkontakte groups. After this social tagging process we can recommend to a particular user relevant groups to join or new friends from interesting groups which have a similar taste. We present some preliminary results and explain how we are going to apply these methods on massive data repositories.

Language: English
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Keywords: бикластеризацияанализ формальных понятийFormal Concept AnalysisтрикластеризацияВеб 2.0 и Social Computingbiclusteringtriclusteringonline social networksWeb 2.0 and social computingонлайн социальные сети

In book

Perspectives in Business Informatics Research. 11th International Conference, BIR 2012, Nizhny Novgorod, Russia, September 2012 Proceedings
Perspectives in Business Informatics Research. 11th International Conference, BIR 2012, Nizhny Novgorod, Russia, September 2012 Proceedings
Issue 128. , Berlin, Heidelberg: Springer, 2012.
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