A Supervised Method of Feature Weighting for Measuring Semantic Relatedness-Reference-Cited by-同舟云学术

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A Supervised Method of Feature Weighting for Measuring Semantic Relatedness

Published:2011 Issue: Volume: Page:222-233
ISSN:0302-9743
Container-title:Advances in Artificial Intelligence
language:
Short-container-title:

Author:

Kennedy Alistair,Szpakowicz Stan

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-21043-3_27

Reference26 articles.

1. Hagiwara, M., Ogawa, Y., Toyama, K.: Supervised synonym acquisition using distributional features and syntactic patterns. Journal of Natural Language Processing 16, 59–83 (2005)

2. Broda, B., Jaworski, D., Piasecki, M.: Parallel, Massive Processing in SuperMatrix – a General Tool for Distributional Semantic Analysis of Corpus. In: Proceedings of the International Multiconference on Computer Science and Information Technology, pp. 373–379 (2010)

3. Snow, R., Jurafsky, D., Ng, A.Y.: Semantic Taxonomy Induction from Heterogenous Evidence. In: Proceedings of COLING/ACL 2006, Sydney, Australia (2006)

4. Fellbaum, C. (ed.): WordNet: an Electronic Lexical Database. MIT Press, Cambridge (1998)

5. Turney, P.D., Pantel, P.: From Frequency to Meaning: Vector Space Models of Semantics. Journal of Artificial Intelligence Research 37, 141–188 (2010)

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