Verb sense disambiguation using support vector machines: Impact of WordNet-extracted features

8Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The disambiguation of verbs is usually considered to be more difficult with respect to other part-of-speech categories. This is due both to the high polysemy of verbs compared with the other categories, and to the lack of lexical resources providing relations between verbs and nouns. One of such resources is WordNet, which provides plenty of information and relationships for nouns, whereas it is less comprehensive with respect to verbs. In this paper we focus on the disambiguation of verbs by means of Support Vector Machines and the use of Word Net-extracted features, based on the hyperonyms of context nouns. © Springer-Verlag Berlin Heidelberg 2006.

Cite

CITATION STYLE

APA

Buscaldi, D., Rosso, P., Pla, F., Segarra, E., & Arnal, E. S. (2006). Verb sense disambiguation using support vector machines: Impact of WordNet-extracted features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3878 LNCS, pp. 192–195). https://doi.org/10.1007/11671299_21

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free