A study of hybrid similarity measures for semantic relation extraction

Authors:
Alexander Panchenko;Olga Morozova
Affiliations:
Université catholique de Louvain, Belgium;Université catholique de Louvain, Belgium
Venue:
HYBRID '12 Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
Year:
2012

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Abstract

This paper describes several novel hybrid semantic similarity measures. We study various combinations of 16 baseline measures based on WordNet, Web as a corpus, corpora, dictionaries, and encyclopedia. The hybrid measures rely on 8 combination methods and 3 measure selection techniques and are evaluated on (a) the task of predicting semantic similarity scores and (b) the task of predicting semantic relation between two terms. Our results show that hybrid measures outperform single measures by a wide margin, achieving a correlation up to 0.890 and MAP(20) up to 0.995.