CoTO: A novel approach for fuzzy aggregation of semantic similarity measures

被引:20
|
作者
Martinez-Gil, Jorge [1 ]
机构
[1] Software Competence Ctr Hagenberg, Hagenberg Im Muhlkreis, Austria
来源
关键词
Knowledge-based analysis; Text mining; Semantic similarity measurement; Fuzzy logic;
D O I
10.1016/j.cogsys.2016.01.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Semantic similarity measurement aims to determine the likeness between two text expressions that use different lexicographies for representing the same real object or idea. There are a lot of semantic similarity measures for addressing this problem. However, the best results have been achieved when aggregating a number of simple similarity measures. This means that after the various similarity values have been calculated, the overall similarity for a pair of text expressions is computed using an aggregation function of these individual semantic similarity values. This aggregation is often computed by means of statistical functions. In this work, we present CoTO (Consensus or Trade-Off) a solution based on fuzzy logic that is able to outperform these traditional approaches. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:8 / 17
页数:10
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