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Erschienen in:
2014 | OriginalPaper | Buchkapitel
User Partitioning Hybrid for Tag Recommendation
verfasst von : Jonathan Gemmell, Bamshad Mobasher, Robin Burke
Erschienen in: User Modeling, Adaptation, and Personalization
Verlag: Springer International Publishing
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Tag recommendation is a fundamental service in today’s social annotation systems, assisting users as they collect and annotate resources. Our previous work has demonstrated the strengths of a linear weighted hybrid, which weights and combines the results of simple components into a final recommendation. However, these previous efforts treated each user the same. In this work, we extend our approach by automatically discovering partitions of users. The user partitioning hybrid learns a different set of weights for these user partitions. Our rigorous experimental results show a marked improvement. Moreover, analysis of the partitions within a dataset offers interesting insights into how users interact with social annotations systems.