WordNet Gloss for Semantic Concept Relatedness

被引：0
|
作者：
Bijaksana, Moch Arif [1 ]
Permadi, Rakhmad Indra [1 ]
机构：
[1] Telkom Univ, Sch Comp, Bandung, Indonesia
来源：
RECENT ADVANCES ON SOFT COMPUTING AND DATA MINING | 2017年 / 549卷
关键词：
Semantic textual relatedness; Semantic textual similarity; Lexical relatedness; Gloss; WordNet; INFORMATION-CONTENT; NEW-MODEL; SIMILARITY;
D O I：
10.1007/978-3-319-51281-5_41
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Semantic lexical similarity and relatedness are important issues in natural language processing (NLP). Similarity and relatedness are not the same, while they are very closely related. To date, in many works these two issues are mixed up which harm system's effectiveness. A popular approach to measure semantic similarity and relatedness is utilizing WordNet, a lexical database. This paper shows that Wordnet's gloss is a potential source for measuring semantic relatedness. Experiment result using WordSim353 relatedness database confirms the effectiveness of the approach.
引用
收藏
页码：406 / 413
页数：8
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