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Eng."],"published-print":{"date-parts":[[2014,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This study examines the ability of a semantic space model to represent the meaning of noun compounds such as \u2018information gathering\u2019 or \u2018heart disease.\u2019 For a semantic space model to compute the meaning and the attributional similarity (or semantic relatedness) for unfamiliar noun compounds that do not occur in a corpus, the vector for a noun compound must be computed from the vectors of its constituent words using vector composition algorithms. Six composition algorithms (i.e., centroid, multiplication, circular convolution, predication, comparison, and dilation) are compared in terms of the quality of the computation of the attributional similarity for English and Japanese noun compounds. To evaluate the performance of the computation of the similarity, this study uses three tasks (i.e., related word ranking, similarity correlation, and semantic classification), and two types of semantic spaces (i.e., latent semantic analysis-based and positive pointwise mutual information-based spaces). The result of these tasks is that the dilation algorithm is generally most effective in computing the similarity of noun compounds, while the multiplication algorithm is best suited specifically for the positive pointwise mutual information-based space. In addition, the comparison algorithm works better for unfamiliar noun compounds that do not occur in the corpus. These findings indicate that in general a semantic space model, and in particular the dilation, multiplication, and comparison algorithms have sufficient ability to compute the attributional similarity for noun compounds.<\/jats:p>","DOI":"10.1017\/s135132491200037x","type":"journal-article","created":{"date-parts":[[2013,1,15]],"date-time":"2013-01-15T11:46:31Z","timestamp":1358250391000},"page":"185-234","source":"Crossref","is-referenced-by-count":4,"title":["A semantic space approach to the computational semantics of noun compounds"],"prefix":"10.1017","volume":"20","author":[{"given":"AKIRA","family":"UTSUMI","sequence":"first","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2013,1,15]]},"reference":[{"key":"S135132491200037X_ref72","doi-asserted-by":"publisher","DOI":"10.1006\/jmla.1996.0024"},{"key":"S135132491200037X_ref67","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1613\/jair.2934","article-title":"From frequency to meaning: vector space models of semantics","volume":"37","author":"Turney","year":"2010","journal-title":"Journal of Artificial Intelligence Research"},{"key":"S135132491200037X_ref66","doi-asserted-by":"publisher","DOI":"10.1162\/coli.2006.32.3.379"},{"key":"S135132491200037X_ref65","first-page":"678","volume-title":"Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL-10)","author":"Tratz","year":"2010"},{"key":"S135132491200037X_ref62","first-page":"247","volume-title":"Proceedings of 40th Annual Meeting of the Association for Computational Linguistics (ACL-02)","author":"Rosario","year":"2002"},{"key":"S135132491200037X_ref61","first-page":"82","volume-title":"Proceedings of the 2001 Conference on Empirical Methods in Natural Language Processing (EMNLP2001)","author":"Rosario","year":"2001"},{"key":"S135132491200037X_ref60","first-page":"210","volume-title":"Proceedings of the 5th International Joint Conference on Natural Language Processing (IJCNLP2011)","author":"Reddy","year":"2011"},{"key":"S135132491200037X_ref59","doi-asserted-by":"publisher","DOI":"10.3758\/BRM.41.3.647"},{"key":"S135132491200037X_ref58","first-page":"71","volume-title":"Handbook of Latent Semantic Analysis","author":"Quesada","year":"2007"},{"key":"S135132491200037X_ref57","volume-title":"Holograhic Reduced Representation: Distributed Representation for Cognitive Structures","author":"Plate","year":"2003"},{"key":"S135132491200037X_ref69","doi-asserted-by":"publisher","DOI":"10.1207\/s15327868ms2003_1"},{"key":"S135132491200037X_ref55","first-page":"621","volume-title":"Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL-09)","author":"\u00d3 S\u00e9aghdha","year":"2009"},{"key":"S135132491200037X_ref54","doi-asserted-by":"publisher","DOI":"10.3115\/1599081.1599163"},{"key":"S135132491200037X_ref64","first-page":"97","article-title":"Automatic word sense discrimination","volume":"24","author":"Sch\u00fctze","year":"1998","journal-title":"Computational Linguistics"},{"key":"S135132491200037X_ref1","doi-asserted-by":"publisher","DOI":"10.3115\/1119282.1119294"},{"key":"S135132491200037X_ref68","volume-title":"Renso Kijunhyo (Free Association Norm)","author":"Umemoto","year":"1969"},{"key":"S135132491200037X_ref15","doi-asserted-by":"publisher","DOI":"10.1006\/jmla.1999.2683"},{"key":"S135132491200037X_ref20","doi-asserted-by":"publisher","DOI":"10.3115\/1621474.1621477"},{"key":"S135132491200037X_ref29","first-page":"491","volume-title":"Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics (COLING-ACL 2006) Main Conference Poster Sessions","author":"Kim","year":"2006"},{"key":"S135132491200037X_ref11","doi-asserted-by":"publisher","DOI":"10.2307\/1130176"},{"key":"S135132491200037X_ref44","doi-asserted-by":"publisher","DOI":"10.1207\/s15516709cog1204_2"},{"key":"S135132491200037X_ref52","unstructured":"Nelson D. , McEvoy C. , and Schreiber T. 1998. 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