Name
Abstract | ||
|---|---|---|
This paper describes that a graph-based co-clustering approach is suitable for extraction of verb synonyms from large scale texts. The proposedbipartite graph algorithm can produce clusters of verb synonyms as wellas noun synonyms taking into account word co-occurrence between verb andits argument.Experimental results show that the co-clustering approachachieve higher accuracy than those by a vector-based single clusteringapproach that are usually used for construction of thesaurus. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ISUC.2008.66 | ISUC |
Keywords | Field | DocType |
verb synonym,large scale text,vector-based single clusteringapproach,proposedbipartite graph algorithm,account word co-occurrence,graph-based co-clustering approach,co-clustering approach,verb andits argument,co-clustering approachachieve,higher accuracy,natural language processing,clustering,helium,mutual information,noun,co clustering,data mining,text analysis,graph theory,bipartite graph,accuracy | Graph theory,Verb,Pattern recognition,Computer science,Synonym,Bipartite graph,Noun,Artificial intelligence,Natural language processing,Mutual information,Biclustering,Cluster analysis | Conference |
Citations | PageRank | References |
1 | 0.39 | 4 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Koichi Takeuchi | 1 | 1 | 1.06 |