Semantic Search Exploiting Formal Concept Analysis, Rough Sets, and Wikipedia

Yuncheng Jiang and Mingxuan Yang
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Yuncheng Jiang: School of Computer Science, South China Normal University, Guangzhou, China
Mingxuan Yang: South China Normal University, Guangzhou, China

International Journal on Semantic Web and Information Systems (IJSWIS), 2018, vol. 14, issue 3, 99-119

Abstract: This article describes how the traditional web search is essentially based on a combination of textual keyword searches with an importance ranking of the documents depending on the link structure of the web. However, one of the dimensions that has not been captured to its full extent is that of semantics. Currently, combining search and semantics gives birth to the idea of the semantic search. The purpose of this article is to present some new methods to semantic search to solve some shortcomings of existing approaches. Concretely, the authors propose two novel methods to semantic search by combining formal concept analysis, rough set theory, and similarity reasoning. In particular, the authors use Wikipedia to compute the similarity of concepts (i.e., keywords). The experimental results show that the authors' proposals perform better than some of the most representative similarity search methods and sustain the intuitions with respect to human judgements.

Date: 2018
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