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Semantic relatedness algorithm for keyword sets of geographic metadata
Chen, Zugang1; Yang, Yaping2
2019-09-16
Source PublicationCARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE
ISSN1523-0406
Pages16
Corresponding AuthorYang, Yaping(yangyp@igsnrr.ac.cn)
AbstractAdvances in linked geospatial data, recommender systems, and geographic information retrieval have led to urgent necessity to assess the overall semantic relatedness between keyword sets of geographic metadata. In this study, a new model is proposed for computing the semantic relatedness between arbitrary two keyword sets of geographic metadata stored in current global spatial data infrastructures. In this model, the overall semantic relatedness is derived by pairing these keywords that are found to be most relevant to each other and averaging their relatedness. To find the most relevant keywords across two keyword sets precisely, the keywords in the keyword set of geographic metadata are divided into three kinds: the thesaurus elements, the WordNet elements, and the statistical elements. The thesaurus-lexical relatedness measure (TLRM), the extended thesaurus-lexical relatedness measure (ETLRM), and the Longest Common Substring method are proposed to compute the semantic relatedness between two thesaurus elements, two WordNet elements, a thesaurus element, and a WordNet element and two statistical elements, respectively. A human data set - the geographic-metadata's keyword set relatedness dataset, which was used to evaluate the precision of the semantic relatedness measures of keyword sets of geographic metadata, was created. The proposed method was evaluated against the human-generated relatedness judgments and was compared with the Jaccard method and Vector Space Model. The results demonstrated that the proposed method achieved a high correlation with human judgments and outperformed the existing methods. Finally, the proposed method was applied to quantitatively linked geospatial data.
KeywordGeographic metadata keyword sets semantic relatedness knowledge-based method linked geospatial data
DOI10.1080/15230406.2019.1647797
WOS KeywordINTERRATER RELIABILITY ; GEOSPATIAL DATA ; SIMILARITY ; INFORMATION ; SEARCH ; CONTEXT ; SYSTEM
Indexed BySCI
Language英语
Funding ProjectNational Earth System Science Data Sharing Infrastructure[2005DKA32300] ; National Natural Science Foundation of China[41631177] ; Construction Project of Ecological Risk Assessment and Basic Geographic Information Data-base of International Economic Corridor Across China, Mongolia and Russia[131A11KYSB20160091] ; Multidisciplinary Joint Expedition For China-Mongolia-Russia Economic Corridor[2017FY101300] ; Branch Center Project of Geography, Resources and Ecology of Knowledge Center for Chi-nese Engineering Sciences and Technology[CKCEST-2017-1-8]
Funding OrganizationNational Earth System Science Data Sharing Infrastructure ; National Natural Science Foundation of China ; Construction Project of Ecological Risk Assessment and Basic Geographic Information Data-base of International Economic Corridor Across China, Mongolia and Russia ; Multidisciplinary Joint Expedition For China-Mongolia-Russia Economic Corridor ; Branch Center Project of Geography, Resources and Ecology of Knowledge Center for Chi-nese Engineering Sciences and Technology
WOS Research AreaGeography
WOS SubjectGeography
WOS IDWOS:000487016300001
PublisherTAYLOR & FRANCIS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/69570
Collection中国科学院地理科学与资源研究所
Corresponding AuthorYang, Yaping
Affiliation1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Chen, Zugang,Yang, Yaping. Semantic relatedness algorithm for keyword sets of geographic metadata[J]. CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE,2019:16.
APA Chen, Zugang,&Yang, Yaping.(2019).Semantic relatedness algorithm for keyword sets of geographic metadata.CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE,16.
MLA Chen, Zugang,et al."Semantic relatedness algorithm for keyword sets of geographic metadata".CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE (2019):16.
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