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ISPRS Int. J. Geo-Inf. 2018, 7(3), 98; https://doi.org/10.3390/ijgi7030098

An Approach to Measuring Semantic Relatedness of Geographic Terminologies Using a Thesaurus and Lexical Database Sources

1,2,3
,
1,2
and
1,2,4,*
1
State Key Laboratory of Resources and Environmental Information System, Beijing 100101, China
2
Institute of Geographic Sciences and Natural Resources research, Chinese Academy of Sciences, Beijing 100101, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Received: 12 December 2017 / Revised: 2 March 2018 / Accepted: 12 March 2018 / Published: 13 March 2018
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Abstract

In geographic information science, semantic relatedness is important for Geographic Information Retrieval (GIR), Linked Geospatial Data, geoparsing, and geo-semantics. But computing the semantic similarity/relatedness of geographic terminology is still an urgent issue to tackle. The thesaurus is a ubiquitous and sophisticated knowledge representation tool existing in various domains. In this article, we combined the generic lexical database (WordNet or HowNet) with the Thesaurus for Geographic Science and proposed a thesaurus–lexical relatedness measure (TLRM) to compute the semantic relatedness of geographic terminology. This measure quantified the relationship between terminologies, interlinked the discrete term trees by using the generic lexical database, and realized the semantic relatedness computation of any two terminologies in the thesaurus. The TLRM was evaluated on a new relatedness baseline, namely, the Geo-Terminology Relatedness Dataset (GTRD) which was built by us, and the TLRM obtained a relatively high cognitive plausibility. Finally, we applied the TLRM on a geospatial data sharing portal to support data retrieval. The application results of the 30 most frequently used queries of the portal demonstrated that using TLRM could improve the recall of geospatial data retrieval in most situations and rank the retrieval results by the matching scores between the query of users and the geospatial dataset. View Full-Text
Keywords: geographic terminology; semantic relatedness; thesaurus; lexical databases; thesaurus–lexical relatedness measure (TLRM); Geospatial Information Retrieval (GIR) geographic terminology; semantic relatedness; thesaurus; lexical databases; thesaurus–lexical relatedness measure (TLRM); Geospatial Information Retrieval (GIR)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Chen, Z.; Song, J.; Yang, Y. An Approach to Measuring Semantic Relatedness of Geographic Terminologies Using a Thesaurus and Lexical Database Sources. ISPRS Int. J. Geo-Inf. 2018, 7, 98.

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