A comparison of models of word meaning in context

作者: Stefan Thater , Georgiana Dinu , Soeren Laue

DOI:

关键词:

摘要: This paper compares a number of recently proposed models for computing context sensitive word similarity. We clarify the connections between these models, simplify their formulation and evaluate them in unified setting. show that are essentially equivalent if syntactic information is ignored, substantial performance differences previously reported disappear to large extent when simplified variants evaluated under identical conditions. Furthermore, our reformulation allows design straightforward fast implementation.

参考文章(12)
Georgiana Dinu, Mirella Lapata, Measuring Distributional Similarity in Context empirical methods in natural language processing. pp. 1162- 1172 ,(2010)
Ioannis Klapaftis, Diana McCarthy, Suresh Manandhar, Siva Reddy, Dynamic and Static Prototype Vectors for Semantic Composition international joint conference on natural language processing. pp. 705- 713 ,(2011)
P. D. Turney, P. Pantel, From frequency to meaning: vector space models of semantics Journal of Artificial Intelligence Research. ,vol. 37, pp. 141- 188 ,(2010) , 10.1613/JAIR.2934
Katrin Erk, Sebastian Padó, A structured vector space model for word meaning in context Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08. pp. 897- 906 ,(2008) , 10.3115/1613715.1613831
Katrin Erk, Sebastian Padó, Paraphrase Assessment in Structured Vector Space: Exploring Parameters and Datasets Proceedings of the Workshop on Geometrical Models of Natural Language Semantics. pp. 57- 65 ,(2009) , 10.3115/1705415.1705423
Manfred Pinkal, Stefan Thater, Hagen Fürstenau, Contextualizing Semantic Representations Using Syntactically Enriched Vector Models meeting of the association for computational linguistics. pp. 948- 957 ,(2010)
Mirella Lapata, Jeff Mitchell, Vector-based Models of Semantic Composition meeting of the association for computational linguistics. pp. 236- 244 ,(2008)
Sebastian Pado, Katrin Erk, Exemplar-Based Models for Word Meaning in Context meeting of the association for computational linguistics. pp. 92- 97 ,(2010)
Thierry Poibeau, Anna Korhonen, Tim Van de Cruys, Latent Vector Weighting for Word Meaning in Context empirical methods in natural language processing. pp. 1012- 1022 ,(2011)
Joseph Reisinger, Raymond J. Mooney, Multi-Prototype Vector-Space Models of Word Meaning north american chapter of the association for computational linguistics. pp. 109- 117 ,(2010)