A Study of Hybrid Similarity Measures for Semantic Relation Extraction

This paper describes several novel hybrid semantic similarity measures. We study various combinations of 16 baseline mea- sures based on WordNet, Web as a cor- pus, corpora, dictionaries, and encyclope- dia. The hybrid measures rely on 8 com- bination 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 mea- sures by a wide margin, achieving a correla- tion up to 0.890 and MAP(20) up to 0.995