{"title":"基于扩展WordNet的词义消歧","authors":"S. Naskar, Sivaji Bandyopadhyay","doi":"10.1109/ICCTA.2007.134","DOIUrl":null,"url":null,"abstract":"In this paper we propose an Extended WordNet based word sense disambiguation algorithm for disambiguating nouns, verbs and adjectives. The algorithm is inspired by the Lesk algorithm and involves looking for overlaps between the context of a word in a sentence and the contexts constructed from the WordNet. The algorithm relies on the sense tagged synset glosses provided by the Extended WordNet. The system has been evaluated on the first 10 Semcor 2.0 files and produces a precision of 85.9%, and 62.1% recall","PeriodicalId":308247,"journal":{"name":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Word Sense Disambiguation Using Extended WordNet\",\"authors\":\"S. Naskar, Sivaji Bandyopadhyay\",\"doi\":\"10.1109/ICCTA.2007.134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose an Extended WordNet based word sense disambiguation algorithm for disambiguating nouns, verbs and adjectives. The algorithm is inspired by the Lesk algorithm and involves looking for overlaps between the context of a word in a sentence and the contexts constructed from the WordNet. The algorithm relies on the sense tagged synset glosses provided by the Extended WordNet. The system has been evaluated on the first 10 Semcor 2.0 files and produces a precision of 85.9%, and 62.1% recall\",\"PeriodicalId\":308247,\"journal\":{\"name\":\"2007 International Conference on Computing: Theory and Applications (ICCTA'07)\",\"volume\":\"157 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computing: Theory and Applications (ICCTA'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCTA.2007.134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computing: Theory and Applications (ICCTA'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCTA.2007.134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we propose an Extended WordNet based word sense disambiguation algorithm for disambiguating nouns, verbs and adjectives. The algorithm is inspired by the Lesk algorithm and involves looking for overlaps between the context of a word in a sentence and the contexts constructed from the WordNet. The algorithm relies on the sense tagged synset glosses provided by the Extended WordNet. The system has been evaluated on the first 10 Semcor 2.0 files and produces a precision of 85.9%, and 62.1% recall
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