A Study of Hybrid Similarity Measures for Semantic Relation Extraction

Panchenko, Alexander;Fairon, Cédrick;Morozova, Olga
(2012) Workshop of Innovative Hybrid Approaches to the Processing of Textual Data Workshop of European Chapter of the Association for Computational Linguistics (EACL) — Location: Avignon, France (23.April.2012)

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Authors
  • Panchenko, AlexanderUCLouvain
    Author
  • Fairon, CédrickUCLouvain
    Collaborator
  • Morozova, OlgaUCLouvain
    Author
Abstract
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.
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Panchenko, A., & Morozova, O. (2012). A Study of Hybrid Similarity Measures for Semantic Relation Extraction. Workshop of Innovative Hybrid Approaches to the Processing of Textual Data Workshop of European Chapter of the Association for Computational Linguistics (EACL), Avignon, France.