New PDF release: Advances in Artificial Intelligence: 24th Canadian

By Eric Aaron, Juan Pablo Mendoza (auth.), Cory Butz, Pawan Lingras (eds.)

ISBN-10: 3642210422

ISBN-13: 9783642210426

This booklet constitutes the refereed court cases of the twenty fourth convention on synthetic Intelligence, Canadian AI 2011, held in St. John’s, Canada, in may possibly 2011. The 23 revised complete papers offered including 22 revised brief papers and five papers from the graduate scholar symposium have been conscientiously reviewed and chosen from eighty one submissions. The papers disguise a wide variety of issues providing unique paintings in all parts of synthetic intelligence, both theoretical or applied.

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Extra resources for Advances in Artificial Intelligence: 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John’s, Canada, May 25-27, 2011. Proceedings

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Farzindar clustering of candidate patterns for the discovery of the most important relation types among NE’s from a newspaper domain was presented by [9]. In the biomedical domain, most approaches were supervised and relied on regular expressions to learn patterns [5], while semi-supervised approaches exploited pre-defined seed patterns and cue words [11, 17]. Several approaches in IE have relied on dependency trees in order to extract patterns for the automatic acquisition of IE systems [27, 25 and 7].

Under these assumptions, we do not need to worry about the interpretation of predicates and functions outside T . Syntax and Semantics of Aggregate Operators. We may use evaluation for formulas with expansion predicates. By evaluating a formula, which has expansion predicates, as true we mean that there is a solution for the whole specification which satisfies the given formula, too. Also, for sake of representation, we may use φ[¯ a, z¯2 ] as a short-hand for φ(z¯1 , z¯2 )[z¯1 /¯ a], which denotes substituting a ¯ for every occurrence of z¯1 in φ.

In a dependency tree a pattern is defined as a path in the dependency tree passing through zero or more intermediate nodes within a dependency tree [27]. An insight of usefulness of the dependency patterns was provided by [26] in their work as they revealed that dependency parsers have the advantage of generating analyses which abstract away from the surface realisation of text to a greater extent than phrase structure grammars tend to, resulting in semantic information being more accessible in the representation of the text which can be useful for IE.

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Advances in Artificial Intelligence: 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John’s, Canada, May 25-27, 2011. Proceedings by Eric Aaron, Juan Pablo Mendoza (auth.), Cory Butz, Pawan Lingras (eds.)


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