Download Artificial Intelligence An International Perspective: An by John Atkinson, Mauricio Solar (auth.), Max Bramer (eds.) PDF

By John Atkinson, Mauricio Solar (auth.), Max Bramer (eds.)

Artificial Intelligence (AI) is a quickly starting to be inter-disciplinary box with a protracted and exclusive background that consists of many nations and significantly pre-dates the improvement of desktops. it may be traced again no less than so far as historic Greece and has advanced over the years to turn into an important subfield of laptop technology in general.

This cutting-edge survey not just serves as a "position paper" at the box from the point of view of specialist participants of the IFIP Technical Committee 12, its operating teams and their colleagues, but in addition offers overviews of present paintings in several countries.

The chapters describe vital rather new or rising parts of labor within which the authors are in my view concerned, together with textual content and hypertext categorization; self sufficient platforms; affective intelligence; AI in digital healthcare platforms; artifact-mediated society and social intelligence layout; multilingual wisdom administration; brokers, intelligence and instruments; clever consumer profiling; and provide chain company intelligence. they supply an attractive overseas standpoint on the place this crucial box goes on the finish of the 1st decade of the twenty-first century.

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Extra resources for Artificial Intelligence An International Perspective: An International Perspective

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The set of features can be generated either manually or automatically based on a specific document collection, usually the set of training documents used as input for the learning algorithm. A given document vector has, in each component, a numerical value to indicate its importance. This value is expressed as a function of the frequency of the index term in the particular document. By varying this function, we can produce different term weightings. The resulting representation of the text is equivalent to the attribute-value representation, which is commonly used in machine learning.

Boosting Applied to Word Sense Disambiguation. : Towards automatic indexing: automatic assignment of controlled-language indexing and classification from free indexing. : A probabilistic learning approach for document indexing. : Exploiting structural information for text classification on the WWW. , R. Berthold, M. ) IDA 1999. LNCS, vol. 1642, pp. 487– 497. : Experiments on the use of feature selection and negative evidence in automated text categorization. , Baker, T. ) ECDL 2000. LNCS, vol.

Term exists in target page, or a neighbour page, ws(sourcel) is the weight we assign to sourcel, and TF(ti, tagk, sourcel, Dj) is the number of times term ti is present in the tag tagk of the sourcel related to HTML document Dj. ­D if tag META ½ ° ° w t ( tag ) ® E if tag TITLE ¾ °1 if somewhere else ° ¯ ¿ ­G if source ° w s ( source ) ®O if source ° ¯1 if source incoming link ½ ° outgoing link ¾ target web page ¿° The drawback of this approach is that the resulting set of total features (size of the hypertext dictionary) is inflated.

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