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A novel approach to managing the dynamic nature of semantic relatedness

A novel approach to managing the dynamic nature of semantic relatedness
A novel approach to managing the dynamic nature of semantic relatedness
This research proposes a novel method of measuring the dynamics of semantic relatedness. Research on semantic relatedness has a long history in the fields of computational linguistics, psychology, computer science, as well as information systems. Computing semantic relatedness has played a critical role in various situations, such as data integration and keyword recommendation. Many researchers have tried to propose more sophisticated techniques to measure semantic relatedness. However, little research has considered the change of semantic relatedness with the flow of time and occurrence of events. The authors' proposed method is validated by actual corpus data collected from a particular context over a specific period of time. They test the feasibility of our proposed method by constructing semantic networks by using the corpus collected during a different period of time. The experiment results show that our method can detect and manage the changes in semantic relatedness between concepts. Based on the results, the authors discuss the need for a dynamic semantic relatedness paradigm.
Computational linguistics, Computer science, Information systems, Semantic networks, Semantic relatedness
1533-8010
1-26
Choi, Youngseok
928c489e-7c5b-42fc-bad8-77ce717ba106
Oh, Jungsuk
2efb7df3-6c7a-4060-9515-3a574ec20d53
Park, Jinsoo
f7c18d81-7513-42ca-880e-cfca18c9177c
Choi, Youngseok
928c489e-7c5b-42fc-bad8-77ce717ba106
Oh, Jungsuk
2efb7df3-6c7a-4060-9515-3a574ec20d53
Park, Jinsoo
f7c18d81-7513-42ca-880e-cfca18c9177c

Choi, Youngseok, Oh, Jungsuk and Park, Jinsoo (2016) A novel approach to managing the dynamic nature of semantic relatedness. Journal of Database Management, 27 (2), 1-26. (doi:10.4018/JDM.2016040101).

Record type: Article

Abstract

This research proposes a novel method of measuring the dynamics of semantic relatedness. Research on semantic relatedness has a long history in the fields of computational linguistics, psychology, computer science, as well as information systems. Computing semantic relatedness has played a critical role in various situations, such as data integration and keyword recommendation. Many researchers have tried to propose more sophisticated techniques to measure semantic relatedness. However, little research has considered the change of semantic relatedness with the flow of time and occurrence of events. The authors' proposed method is validated by actual corpus data collected from a particular context over a specific period of time. They test the feasibility of our proposed method by constructing semantic networks by using the corpus collected during a different period of time. The experiment results show that our method can detect and manage the changes in semantic relatedness between concepts. Based on the results, the authors discuss the need for a dynamic semantic relatedness paradigm.

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More information

Published date: 1 April 2016
Keywords: Computational linguistics, Computer science, Information systems, Semantic networks, Semantic relatedness

Identifiers

Local EPrints ID: 437733
URI: http://eprints.soton.ac.uk/id/eprint/437733
ISSN: 1533-8010
PURE UUID: d9d1e8af-daf4-4d8b-a292-d384c606d43b
ORCID for Youngseok Choi: ORCID iD orcid.org/0000-0001-9842-5231

Catalogue record

Date deposited: 13 Feb 2020 17:30
Last modified: 14 Feb 2020 01:48

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