Download Advances in Computational Intelligence: 11th Mexican by Grigori Sidorov, Francisco Velasquez, Efstathios Stamatatos, PDF

By Grigori Sidorov, Francisco Velasquez, Efstathios Stamatatos, Alexander Gelbukh (auth.), Ildar Batyrshin, Miguel González Mendoza (eds.)

ISBN-10: 3642377971

ISBN-13: 9783642377976

ISBN-10: 364237798X

ISBN-13: 9783642377983

The two-volume set LNAI 7629 and LNAI 7630 constitutes the refereed lawsuits of the eleventh Mexican foreign convention on man made Intelligence, MICAI 2012, held in San Luis Potosí, Mexico, in October/November 2012. The eighty revised papers offered have been rigorously reviewed and chosen from 224 submissions. the second one quantity comprises forty papers concentrating on delicate computing. The papers are geared up within the following topical sections: typical language processing; evolutionary and nature-inspired metaheuristic algorithms; neural networks and hybrid clever platforms; fuzzy structures and probabilistic versions in choice making.

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Extra resources for Advances in Computational Intelligence: 11th Mexican International Conference on Artificial Intelligence, MICAI 2012, San Luis Potosí, Mexico, October 27 – November 4, 2012. Revised Selected Papers, Part II

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Authorship attribution in the wild. Language Resources and Evaluation 45(1), 83–94 (2011) 20. : Measuring differentiability: unmasking pseudonymous authors. Journal of Machine Learning Research, 1261–1276 (2007) Semantic Annotation for Textual Entailment Recognition Assaf Toledo1 , Sophia Katrenko1, Stavroula Alexandropoulou1 , Heidi Klockmann1 , Asher Stern2 , Ido Dagan2 , and Yoad Winter1 1 Utrecht University, Utrecht, The Netherlands 2 Bar Ilan University, Ramat Gan, Israel Abstract. We introduce a new semantic annotation scheme for the Recognizing Textual Entailment (RTE) dataset as well as a manually annotated dataset that uses this scheme.

Example Consider the following pair from RTE 2: – T: The anti-terrorist court found two men guilty of murdering Shapour Bakhtiar and his secretary Sorush Katibeh, who were found with their throats cut in August 1991. – H: Shapour Bakhtiar died in 1991. The entailment patterns in this example can be explained by appealing to the semantics of APP, CONJ and RMOD, as follows: – APP: The appositive modification in Shapour Bakhtiar and his secretary Sorush Katibeh, who were found with their throats cut in August 1991 licenses the inference that Shapour Bakhtiar and his secretary Sorush Katibeh were found with their throats cut in August 1991.

Example of the feature vector structure of the training data 4 Experimental Results The development and test datasets consist of 400 Text–Hypothesis pairs. The lexical features are calculated for both development and test datasets. Matching scores of the development dataset were used to train the model. The WEKA toolset was used to train the classification model and test the output for the unseen pairs thereafter. The experimental results obtained for both development and text data predicted by the WEKA toolset using the Naïve Bayes as the classification algorithm are as follows.

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