Post-Retrieval Clustering Using Third-Order Similarity Measures

Jose G. Moreno, Gaël Dias and Guillaume Cleuziou

The 51st Annual Meeting of the Association for Computational Linguistics - Short Papers (ACL Short Papers 2013)
Sofia, Bulgaria, August 4-9, 2013

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Abstract

Post-retrieval clustering is the task of clustering Web search results. Within this context, we propose a new methodology that adapts the classical K-means algorithm to a third-order similarity measure initially developed for NLP tasks. Results obtained with the definition of a new stopping criterion over the ODP-239 and the MORESQUE gold standard datasets evidence that our proposal outperforms all reported text-based approaches.

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