To tag or not to tag -: harvesting adjacent metadata in large-scale tagging systems

Authors:
Adriana Budura;Sebastian Michel;Philippe Cudré-Mauroux;Karl Aberer
Affiliations:
EPFL, Lausanne, Switzerland;EPFL, Lausanne, Switzerland;MIT, Cambridge, USA;EPFL, Lausanne, Switzerland
Venue:
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2008

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Abstract

We present HAMLET, a suite of principles, scoring models and algorithms to automatically propagate metadata along edges in a document neighborhood. As a showcase scenario we consider tag prediction in community-based Web 2.0 tagging applications. Experiments using real-world data demonstrate the viability of our approach in large-scale environments where tags are scarce. To the best of our knowledge, HAMLET is the first system to promote an efficient and precise reuse of shared metadata in highly dynamic, large-scale Web 2.0 tagging systems.