Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (5): 66-74    DOI: 10.11925/infotech.2096-3467.2019.1297
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Calculating Word Similarities Based on Formal Concept Analysis
Liu Ping1,2(),Peng Xiaofang1
1School of Information Management, Wuhan University, Wuhan 430072, China
2Institute for Digital Library, Wuhan University, Wuhan 430072, China
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Abstract

[Objective] This paper tries to add a topic layer between document and word layers, aiming to calculate word similarities effectively. [Methods] First, we proposed a topic defintion and representation model based on the theory of formal concept analysis. Then, we mapped words to the topic layer. Finally, we developed an algorithm to calculate word similarities with the help of topic-to-topic relationship.[Results] We analyzed papers of SIGIR conference from 2006 to 2016 with the proposed method to calculate word similarities in the field of information retrieval. The precision and recall of the proposed method were up to 30% and 21% higher than those of the FastText method.[Limitations] The proposed method relies on the quality of extracted feature words of documents.[Conclusions] The proposed method utilizes the semantic relations among associated topics, and effectively calculate word similarities.

Received: 03 December 2019      Published: 15 June 2020
 ZTFLH: TP391.1
Corresponding Authors: Liu Ping     E-mail: pliuleeds@126.com
 The Relationship Among Documents, Topics and Words An Example of Formal Context Table1"> Concept Lattice Based on Table1 The Association Matrix of $T-K$ Based on the Concept Lattice in Fig.2 The Association Matrix of $K-T$ Based on the Concept Lattice in Fig.2 High Frequency Keywords (Top 50) Topic Formal Context (Partial) The Matrix of Topic Similarity (Partial) The Matrix of Words Similarity (Partial) Comparison of Words Similarity Calculation The Calculation Method of Precision and Recall Comparison of Precision Comparison of Recall