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dc:title "HTML Summary of #5039 \n\nExpressing Implicit Semantic Relations without Supervision\n\n";
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bibo:abstract "We present an unsupervised learning algorithm that mines large \ntext corpora for patterns that express implicit semantic relations. \nFor a given input word pair X:Y with some unspecified semantic \nrelations, the corresponding output list of patterns \nis ranked according to how well each pattern Pi expresses the \nrelations between X and Y. For example, given X=ostrich and \nY=bird, the two highest ranking output patterns are \"X is the \nlargest Y\" and \"Y such as the X\". The output patterns are intended \nto be useful for finding further pairs with the same relations, to \nsupport the construction of lexicons, ontologies, and semantic \nnetworks. The patterns are sorted by pertinence, where the pertinence \nof a pattern Pi for a word pair X:Y is the expected relational \nsimilarity between the given pair and typical pairs for Pi. The \nalgorithm is empirically evaluated on two tasks, solving \nmultiple-choice SAT word analogy questions and classifying semantic \nrelations in noun-modifier pairs. On both tasks, the algorithm \nachieves state-of-the-art results, performing significantly better \nthan several alternative pattern ranking algorithms, based on tf-idf."^^xsd:string;
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dct:date "2006";
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skos:prefLabel "Artificial Intelligence" .
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foaf:familyName "Turney"^^xsd:string;
foaf:givenName "Peter D."^^xsd:string;
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