Distributional analysis of related synsets in WordNet* for a word sense disambiguation task

Fragos, K; Maistros, Y

dc.contributor.author	Fragos, K	en
dc.contributor.author	Maistros, Y	en
dc.date.accessioned	2014-03-01T01:22:12Z
dc.date.available	2014-03-01T01:22:12Z
dc.date.issued	2005	en
dc.identifier.issn	0218-2130	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16487
dc.subject	Synsets	en
dc.subject	Word sense disambiguation	en
dc.subject	WordNet	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.title	Distributional analysis of related synsets in WordNet* for a word sense disambiguation task	en
heal.type	journalArticle	en
heal.identifier.primary	10.1142/S0218213005002478	en
heal.identifier.secondary	http://dx.doi.org/10.1142/S0218213005002478	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	This work presents a new method for an unsupervised word sense disambiguation task using WordNet semantic relations. In this method we expand the context of a word being disambiguated with related synsets from the available WordNet relations and study within this set the distribution of the related synset that correspond to each sense of the target word. A single sample Pearson-Chi-Square goodness-of-fit hypothesis test is used to determine whether the null hypothesis of a composite normality PDF is a reasonable assumption for a set of related synsets corresponding to a sense. The calculated p-value from this test is a critical value for deciding the correct sense. The target word is assigned the sense, the related synsets of which are distributed more ""abnormally"" relative to the other sets of the other senses. Our algorithm is evaluated on English lexical sample data from the Senseval-2 word sense disambiguation competition. Three WordNet relations, antonymy, hyponymy and hypernymy give a distributional set of related synsets for the context that was proved quite a good word sense discriminator, achieving comparable results with the system obtained the better results among the other competing participants. © World Scientific Publishing Company.	en
heal.publisher	WORLD SCIENTIFIC PUBL CO PTE LTD	en
heal.journalName	International Journal on Artificial Intelligence Tools	en
dc.identifier.doi	10.1142/S0218213005002478	en
dc.identifier.isi	ISI:000234148400003	en
dc.identifier.volume	14	en
dc.identifier.issue	6	en
dc.identifier.spage	919	en
dc.identifier.epage	934	en