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UPV-SI: Word Sense Induction using Self Term Expansion1

David Pinto$^{(1,2)}$

Paolo Rosso$^1$

(1) Department of Information Systems and Computation, Polytechnic University of Valencia
(2) Faculty of Computer Science, B. Autonomous University of Puebla


In this paper we are reporting the results obtained participating in the ``Evaluating Word Sense Induction and Discrimination Systems'' task of Semeval 2007. Our totally unsupervised system performed an automatic self-term expansion process by mean of co-ocurrence terms and, thereafter, it executed the unsupervised KStar clustering method. Two ranking tables with different evaluation measures were calculated by the task organizers, every table with two baselines and six runs submitted by different teams. We were ranked third place in both ranking tables obtaining a better performance than three different baselines, and outperforming the average score.

David Pinto 2007-05-08