MODELING WORDNET GLOSSES TO PERFORM WORD SENSE DISAMBIGUATION

被引:4
|
作者
Fragos, Kostas [1 ]
机构
[1] Inst Educ Technol, Dept Comp Sci, Athens 12210, Greece
关键词
Word sense disambiguation; WordNet; semantic relatedness; WordNet glosses; senseval; goodness of fit statistical test;
D O I
10.1142/S0218213013500036
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 work, we propose a new measure of semantic relatedness between concepts applied in word sense disambiguation. Using the overlaps between WordNet definitions of concepts (glosses) and the so-called goodness of fit statistical test we establish a formal mechanism for quantifying and estimating the semantic relatedness between concepts. More concretely, we model WordNet glosses overlaps by making a theoretical assumption about their distribution and then we quantify the discrepancy between the theoretical and actual distribution. This discrepancy is suitably used to measure the relatedness between the input concepts. The experimental results showed very good performance on SensEval-2 lexical sample data for word sense disambiguation.
引用
收藏
页数:13
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