Discovering Community of Lingual Practice for Matching Multilingual Tags from Folksonomies

Many existing studies have investigated to discover a variety of co-occurrence patterns between entities (e.g. users, tags and resources) from a folksonomy system. The common purposes among them are (i) to understand collective behaviors between online users and (ii) to provide online services (e.g. tag recommendation and information searching) to users. However, most of the existing studies assume that all tags in the folksonomy should be written in an identical language. In this paper, we focus on analyzing a multilingual folksonomy generated by various lingual practices of online users, and discovering meaningful relationships between multilingual tags (e.g. between 'Seoul' in English and 'Coree' in French) co-occurred in the folksonomy. Thereby, we propose novel methods for (i) identifying lingual practices from user tagging patterns to build a community of lingual practice and (ii) exploiting the tag matchings to extend simple term-based queries. Thus, additional resources tagged by other languages can be retrieved. To evaluate the proposed multilingual tag matching method, we have collected real tagging datasets from several well-known social tagging websites (e.g. Del.icio.us), and applied to translating queries to other languages without any external dictionaries.