Hindi Word Sense Disambiguation Using Semantic Relatedness Measure

被引：0

作者：

Singh, Satyendr ^{[1
]}

Singh, Vivek Kumar ^{[2
]}

Siddiqui, Tanveer J. ^{[1
]}

机构：

[1] Univ Allahabad, Dept Elect & Commun, Allahabad 211002, Uttar Pradesh, India

[2] South Asian Univ, New Delhi, India

来源：

MULTI-DISCIPLINARY TRENDS IN ARTIFICIAL INTELLIGENCE | 2013年 / 8271卷

关键词：

Hindi Word Sense Disambiguation; Semantic Relatedness; Semantic Similarity; Semantic Distance; CONTEXT;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we propose and evaluate a method of Hindi word sense disambiguation that computes similarity based on the semantics. We adapt an existing measure for semantic relatedness between two lexically expressed concepts of Hindi WordNet. This measure is based on the length of paths between noun concepts in an is-a hierarchy. Instead of relying on direct overlap the algorithm uses Hindi WordNet hierarchy to learn semantics of words and exploits it in the disambiguation process. Evaluation is performed on a sense tagged dataset consisting of 20 polysemous Hindi nouns. We obtained an overall average accuracy of 60.65% using this measure.

引用

页码：247 / 256

页数：10

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