Word clustering is important for automatic thesaurus construction, text classification, and word sense disambiguation. Recently, several studies have reported using the web as a c...
Yutaka Matsuo, Takeshi Sakaki, Koki Uchiyama, Mits...
An approach to simultaneous document classification and word clustering is developed using a two-way mixture model of Poisson distributions. Each document is represented by a vect...
Proposals for text classification and information retrieval have been recently presented making use of the WordNet ontology. Generally, this methodology requires statistical induc...
Abstract. We describe a semantic clustering method designed to address shortcomings in the common bag-of-words document representation for functional semantic classification tasks....
Many applications dealing with textual information require classification of words into semantic classes (or concepts). However, manually constructing semantic classes is a tediou...