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Imagining the thinking machine: technological myths and the rise of Artificial Intelligence
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New York Yankees and Hollywood Anglos: the persistence of anglo-conformity in the American motion picture industry
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A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs
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In: Ballatore, Andrea; Bertolotto, Michela; & Wilson, David C. (2015). A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs. ISPRS International Journal of Geo-Information, 4(2). UC Santa Barbara: Retrieved from: http://www.escholarship.org/uc/item/9zx1b95k (2015)
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An evaluative baseline for geo-semantic relatedness and similarity
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An evaluative baseline for geo-semantic relatedness and similarity
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Abstract:
In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer’s semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity.
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Keyword:
Computer Science; Psychology
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URL: http://mural.maynoothuniversity.ie/4757/
http://mural.maynoothuniversity.ie/4757/1/2014-An%20evaluative%20baseline%20for%20geo-semantic%20relatedness%20and%20similarity-Ballatore%20et%20al.pdf
http://link.springer.com/article/10.1007/s10707-013-0197-8
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The semantic similarity ensemble
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In: Journal of Spatial Information Science (2013)
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Computing the semantic similarity of geographic terms using volunteered lexical definitions
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The Similarity Jury: Combining expert judgements on geographic concepts
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