UOY: a hypergraph model for word sense induction & disambiguation
I. Klapaftis, and S. Manandhar. Proceedings of the 4th International Workshop on Semantic Evaluations, page 414--417. Stroudsburg, PA, USA, Association for Computational Linguistics, (2007)
Abstract
This paper is an outcome of ongoing research and presents an unsupervised method for automatic word sense induction (WSI) and disambiguation (WSD). The induction algorithm is based on modeling the cooccurrences of two or more words using hypergraphs. WSI takes place by detecting high-density components in the cooccurrence hypergraphs. WSD assigns to each induced cluster a score equal to the sum of weights of its hyperedges found in the local context of the target word. Our system participates in SemEval-2007 word sense induction and discrimination task.
%0 Conference Paper
%1 uoy2007
%A Klapaftis, Ioannis P.
%A Manandhar, Suresh
%B Proceedings of the 4th International Workshop on Semantic Evaluations
%C Stroudsburg, PA, USA
%D 2007
%I Association for Computational Linguistics
%K 2007 based clustering graph semeval sense uoy word wsi
%P 414--417
%T UOY: a hypergraph model for word sense induction & disambiguation
%U http://dl.acm.org/citation.cfm?id=1621474.1621566
%X This paper is an outcome of ongoing research and presents an unsupervised method for automatic word sense induction (WSI) and disambiguation (WSD). The induction algorithm is based on modeling the cooccurrences of two or more words using hypergraphs. WSI takes place by detecting high-density components in the cooccurrence hypergraphs. WSD assigns to each induced cluster a score equal to the sum of weights of its hyperedges found in the local context of the target word. Our system participates in SemEval-2007 word sense induction and discrimination task.
@inproceedings{uoy2007,
abstract = {This paper is an outcome of ongoing research and presents an unsupervised method for automatic word sense induction (WSI) and disambiguation (WSD). The induction algorithm is based on modeling the cooccurrences of two or more words using hypergraphs. WSI takes place by detecting high-density components in the cooccurrence hypergraphs. WSD assigns to each induced cluster a score equal to the sum of weights of its hyperedges found in the local context of the target word. Our system participates in SemEval-2007 word sense induction and discrimination task.},
acmid = {1621566},
added-at = {2011-09-19T03:36:32.000+0200},
address = {Stroudsburg, PA, USA},
author = {Klapaftis, Ioannis P. and Manandhar, Suresh},
biburl = {https://www.bibsonomy.org/bibtex/2c7e2e09c83e0ea170b486cc37501e0b4/jil},
booktitle = {Proceedings of the 4th International Workshop on Semantic Evaluations},
interhash = {05f1fa793925a89793b86dc6aaf4db90},
intrahash = {c7e2e09c83e0ea170b486cc37501e0b4},
keywords = {2007 based clustering graph semeval sense uoy word wsi},
location = {Prague, Czech Republic},
numpages = {4},
pages = {414--417},
publisher = {Association for Computational Linguistics},
series = {SemEval '07},
timestamp = {2013-11-23T20:11:51.000+0100},
title = {UOY: a hypergraph model for word sense induction \& disambiguation},
url = {http://dl.acm.org/citation.cfm?id=1621474.1621566},
year = 2007
}