Paper: Hypernym Discovery Based on Distributional Similarity and Hierarchical Structures

ACL ID D09-1097
Title Hypernym Discovery Based on Distributional Similarity and Hierarchical Structures
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

This paper presents a new method of devel- oping a large-scale hyponymy relation data- base by combining Wikipedia and other Web documents. We attach new words to the hy- ponymy database extracted from Wikipedia by using distributional similarity calculated from documents on the Web. For a given tar- get word, our algorithm first finds k similar words from the Wikipedia database. Then, the hypernyms of these k similar words are assigned scores by considering the distribu- tional similarities and hierarchical distances in the Wikipedia database. Finally, new hy- ponymy relations are output according to the scores. In this paper, we tested two distribu- tional similarities. One is based on raw verb- noun dependencies (which we call “RVD”), and the other is based on a large-scal...