Data

Abstract

: [ Objective ] This paper analyzes the popular text similarity measures and discusses their latest developments. [ Coverage ] We retrieved 69 key articles from CNKI and Web of Science databases by searching “TI: ‘text similarity’ or ‘semantic similarity’ or ‘lexical similarity’ ” in Chinese and English respectively. [ Methods ] We systematically reviewed the text similarity measures focusing on their basic concepts, characteristics and future directions. [ Results ] There were four types of text similarity measures: String-based, Corpus-based, Knowledge-based and others. Measures based on the neural network, Knowledge-based measures and inter-disciplinary measures could be the future research directions. [ Limitations ] We did not discuss the applications of those measures. [ Conclusions ] This paper is a comprehensive review of text similarity measure research.