On Deriving Tagsonomies: Keyword Relations Coming from Crowd

Authors:
Michal Barla;Mária Bieliková
Affiliations:
Institute of Informatics and Software Engineering, Faculty of Informatics and Information Technologies, Slovak University of Technology, Bratislava, Slovakia 842 16;Institute of Informatics and Software Engineering, Faculty of Informatics and Information Technologies, Slovak University of Technology, Bratislava, Slovakia 842 16
Venue:
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Year:
2009

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Abstract

Many keyword-based approaches to text classification, information retrieval or even user modeling for adaptive web-based system could benefit from knowledge on relations between various keywords, which gives further possibilities to compare them, evaluate their distance etc. This paper proposes an approach how to determine keyword relations (mainly a parent-child relationship) by leveraging collective wisdom of the masses, present in data of collaborative (social) tagging systems on the Web. The feasibility of our approach is demonstrated on the data coming from the social bookmarking systems delicious and CiteULike.