Paper: Using Hidden Markov Random Fields to Combine Distributional and Pattern-Based Word Clustering

ACL ID C08-1051
Title Using Hidden Markov Random Fields to Combine Distributional and Pattern-Based Word Clustering
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

Word clustering is a conventional and im- portant NLP task, and the literature has suggested two kinds of approaches to this problem. One is based on the distribu- tional similarity and the other relies on the co-occurrence of two words in lexico- syntactic patterns. Although the two meth- ods have been discussed separately, it is promising to combine them since they are complementary with each other. This pa- per proposes to integrate them using hid- den Markov random fields and demon- strates its effectiveness through experi- ments.