Matching multilingual tags based on community of lingual practice from multiple folksonomy: a preliminary result

Authors:
Jason J. Jung
Affiliations:
Knowledge Engineering Laboratory, Department of Computer Engineering, Yeungnam University, Gyeongsan, Korea
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Year:
2010

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Abstract

By taking into account various co-occurence patterns from a folksonomy, semantic correspondences between tags have been discovered and applied to a number of applications (e.g., recommendation). In this paper, we propose a novel collective intelligence application for expanding and transforming queries for searching for multilingual resources. Thereby, multilingual tags (e.g., between 'Seoul' in English and 'Coree' in French) within a folksonomy have been analyzed whether they have a significant relationship or not. We have tested the proposed multilingual tag matching method by collecting real-world tagging information from several well-known social tagging websites (e.g., Del.icio.us), and applied to translating queries to other languages without any external dictionary.