A Study of Hybrid Similarity Measures for Semantic Relation Extraction
Alexander Panchenko, Olga N. Morozova · 2012
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.