Graph-based clustering for computational linguistics: A survey

Zheng Chen, Heng Ji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this survey we overview graph-based clustering and its applications in computational linguistics. We summarize graph-based clustering as a five-part story: hypothesis, modeling, measure, algorithm and evaluation. We then survey three typical NLP problems in which graph-based clustering approaches have been successfully applied. Finally, we comment on the strengths and weaknesses of graph-based clustering and envision that graph-based clustering is a promising solution for some emerging NLP problems.

Original languageEnglish (US)
Title of host publicationACL 2010 - TextGraphs 2010
Subtitle of host publication2010 Workshop on Graph-Based Methods for Natural Language Processing, Proceedings of the Workshop
Pages1-9
Number of pages9
StatePublished - Dec 1 2010
Externally publishedYes
Event5th Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs 2010 - Uppsala, Sweden
Duration: Jul 16 2010Jul 16 2010

Publication series

NameACL 2010 - TextGraphs 2010: 2010 Workshop on Graph-Based Methods for Natural Language Processing, Proceedings of the Workshop

Conference

Conference5th Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs 2010
CountrySweden
CityUppsala
Period7/16/107/16/10

ASJC Scopus subject areas

  • Software

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  • Cite this

    Chen, Z., & Ji, H. (2010). Graph-based clustering for computational linguistics: A survey. In ACL 2010 - TextGraphs 2010: 2010 Workshop on Graph-Based Methods for Natural Language Processing, Proceedings of the Workshop (pp. 1-9). (ACL 2010 - TextGraphs 2010: 2010 Workshop on Graph-Based Methods for Natural Language Processing, Proceedings of the Workshop).