{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T14:45:58Z","timestamp":1776264358169,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2015,4,1]],"date-time":"2015-04-01T00:00:00Z","timestamp":1427846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001602","name":"Science Foundation Ireland","doi-asserted-by":"publisher","award":["07\/SRC\/I1168"],"award-info":[{"award-number":["07\/SRC\/I1168"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web\u2019s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS). This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects.<\/jats:p>","DOI":"10.3390\/ijgi4020471","type":"journal-article","created":{"date-parts":[[2015,4,7]],"date-time":"2015-04-07T03:47:46Z","timestamp":1428378466000},"page":"471-492","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs"],"prefix":"10.3390","volume":"4","author":[{"given":"Andrea","family":"Ballatore","sequence":"first","affiliation":[{"name":"Center for Spatial Studies, University of California, Santa Barbara, CA 93106, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michela","family":"Bertolotto","sequence":"additional","affiliation":[{"name":"School of Computer Science and Informatics, University College Dublin, Dublin 4, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Wilson","sequence":"additional","affiliation":[{"name":"Department of Software and Information Systems, University of North Carolina, Charlotte, NC 28223, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,4,1]]},"reference":[{"key":"ref_1","unstructured":"Chein, M., and Mugnier, M. 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