Title
Co-Clustering With Recursive Elimination For Verb Synonym Extraction From Large Text Corpus
Abstract
The extraction of verb synonyms is a key technology to build a verb dictionary as a language resource. This paper presents a co-clustering-based verb synonym extraction approach that increases the number of extracted meanings of polysemous verbs from a large text corpus. For verb synonym extraction with a Clustering approach dealing with polysemous verbs can be one problem issue because each polysemous verb should be categorized into different clusters depending on each meanings thus there is a high possibility of failing to extract sonic of the meanings of polysemous verbs. Our proposed approach can extract the different meanings of polysemous verbs by recursively eliminating the extracted Clusters from the initial data set. The experimental results of verb synonym extraction show that the proposed approach increases the correct verb clusters by about 50% with a 0.9% increase in precision and a 1.5% increase in recall over the previous approach.
Year
DOI
Venue
2009
10.1587/transinf.E92.D.2334
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Keywords
Field
DocType
verb synonyms, co-clustering, polysemy, recursive elimination
Verb,Computer science,Synonym,Text corpus,Natural language processing,Artificial intelligence,Biclustering,Cluster analysis,Agrégation,Recursion,Polysemy
Journal
Volume
Issue
ISSN
E92D
12
1745-1361
Citations 
PageRank 
References 
0
0.34
6
Authors
2
Name
Order
Citations
PageRank
Koichi Takeuchi111.06
Hideyuki Takahashi200.34