Hindi Word Sense Disambiguation Using Cosine Similarity

被引：2

作者：

Sarika, D. K. ^{[1
]}

Sharma, Dilip Kumar ^{[1
]}

机构：

[1] GLA Univ, Dept Comp Engn & Applicat, Mathura, India

来源：

PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ICT FOR SUSTAINABLE DEVELOPMENT ICT4SD 2015, VOL 2 | 2016年 / 409卷

关键词：

Word sense disambiguation; Natural language processing; Ambiguity; Hindi WordNet; Cosine similarity;

D O I：

10.1007/978-981-10-0135-2_76

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Hindi is the regional language of India. Most of the people access, retrieve, and share documents in Hindi language. As all the natural languages possess property of being ambiguous, so does Hindi language, which creates obstacles in usage of information technology properly. In order to remove ambiguity from Hindi language, we need a system called Hindi word sense disambiguation (HWSD). In this paper, we present a supervised method, called HWSD using cosine similarity in which vectors are created for testing query and sense knowledge data for the ambiguous word by considering weights. Experiment is performed on dataset consisting of 90 Hindi ambiguous words and it is found that this method outperforms Lesk's algorithm which is well known algorithm for Word sense disambiguation (WSD). We obtained an overall average precision of 78.99 % and average recall of 72.58 %.

引用

页码：801 / 808

页数：8

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