UPV-SI: Word Sense Induction using Self Term Expansion1
(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.