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IMCSIT
2010

Evaluation of Clustering Algorithms for Polish Word Sense Disambiguation

8 years 10 months ago
Evaluation of Clustering Algorithms for Polish Word Sense Disambiguation
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. Thus, this work focuses on evaluation of a few selected clustering algorithms in task of Word Sense Disambiguation for Polish. We tested 6 clustering algorithms (K-Means, K-Medoids, hierarchical agglomerative clustering, hierarchical divisive clustering, Growing Hierarchical Self Organising Maps, graph-partitioning based clustering) and five weighting schemes. For agglomerative and divisive algorithm 13 criterion function were tested. The achieved results are interesting, because best clustering algorithms are close in terms of cluster purity to precision of supervised clustering algorithm on the same dataset, using the same features.
Bartosz Broda, Wojciech Mazur
Added 05 Mar 2011
Updated 05 Mar 2011
Type Journal
Year 2010
Where IMCSIT
Authors Bartosz Broda, Wojciech Mazur
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