Research Area:  Machine Learning

Abstract:

Text similarity measurement is the basis of natural language processing tasks, which play an important role in information retrieval, automatic question answering, machine translation, dialogue systems, and document matching. This paper systematically combs the research status of similarity measurement, analyzes the advantages and disadvantages of current methods, develops a more comprehensive classification description system of text similarity measurement algorithms, and summarizes the future development direction. With the aim of providing reference for related research and application, the text similarity measurement method is described by two aspects: text distance and text representation. The text distance can be divided into length distance, distribution distance, and semantic distance; text representation is divided into string-based, corpus-based, single-semantic text, multi-semantic text, and graph-structure-based representation. Finally, the development of text similarity is also summarized in the discussion section

Keywords:  

Author(s) Name:   Jiapeng Wang and Yihong Dong

Publisher name:  MDPI

DOI:  10.3390/info11090421

Volume Information:   Volume 11 Issue 9

Paper Link:   https://www.mdpi.com/2078-2489/11/9/421