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dc.contributorDepartment of Computing-
dc.creatorXu, J-
dc.creatorLu, Q-
dc.creatorLiu, Z-
dc.identifier.isbn978-1-937284-21-3 (v.1)-
dc.identifier.isbn978-1-937284-22-0 (v.2)-
dc.publisherAssociation for Computational Linguistics (ACL)en_US
dc.rights©Association for Computational Linguisticsen_US
dc.rightsReproduced with permission of the author.en_US
dc.titlePolyUCOMP : combining semantic vectors with skip bigrams for semantic textual similarityen_US
dc.typeConference Paperen_US
dcterms.abstractThis paper presents the work of the Hong Kong Polytechnic University (PolyUCOMP) team which has participated in the Semantic Textual Similarity task of SemEval-2012. The PolyUCOMP system combines semantic vectors with skip bigrams to determine sentence similarity. The semantic vector is used to compute similarities between sentence pairs using the lexical database WordNet and the Wikipedia corpus. The use of skip bigram is to introduce the order of words in measuring sentence similarity.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation*SEM 2012: The First Joint Conference on Lexical and Computational Semantics, June 7-8, 2012, Montre´al, Canada, p. 524–528-
dc.description.ros2011-2012 > Academic research: refereed > Refereed conference paper-
dc.description.oaVersion of Recorden_US
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