Word Sense Induction Using Lexical Chain based Hypergraph Model
Tao Qian, Donghong Ji, Mingyao Zhang, Chong Teng, Congling Xia · 2014
Word Sense Induction is a task of automatically finding word senses from large scale texts. It is general-ly considered as an unsupervised clustering problem. This paper introduces a hypergraph model in which nodes represent instances of contexts where a target word occurs and hyperedges represent high-er-order semantic relatedness among instances. A lexical chain based method is used for discovering the hyperedges, and hypergraph clustering methods are used for finding word senses among the context in-stances. Experiments show that this model outperforms other methods in supervised evaluation and achieves comparable performance with other methods in unsupervised evaluation. 1