How Context and Semantic Information Can Help a Machine Learning System?

Author:

Vázquez Sonia,Kozareva Zornitsa,Montoyo Andrés

Publisher

Springer Berlin Heidelberg

Reference10 articles.

1. Magnini, B., Strapparava, C.: Experiments in word domain disambiguation for paralell texts. In: Proceedings of SIGLEX. Workshop on Word Senses and Multi-linguality (2000)

2. Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., Harshman, R.A.: Indexing by latent semantic analysis. JASIS 41(6), 391–407 (1990)

3. Lecture Notes in Artificial Intelligence;J.J. Webster,2006

4. Kozareva, Z., Vázquez, S., Montoyo, A.: The usefulness of conceptual representation for the identification of semantic variability expressions. In: CICLing, pp. 325–336 (2007)

5. Magnini, B., Cavaglià, G.: Integrating subject field codes into wordnet. In: Gavrilidou, M., Crayannis, G., Markantonatu, S., Piperidis, S., Stainhaouer, G. (eds.) Second International Conference on Language Resources Proceedings of LREC-2000 and Greece Evaluation, Athens, pp. 1413–1418 (2000)

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