Advances in Intelligent Information Systems by François Rioult, Bruno Zanuttini, Bruno Crémilleux (auth.),

By François Rioult, Bruno Zanuttini, Bruno Crémilleux (auth.), Zbigniew W. Ras, Li-Shiang Tsay (eds.)

Intelligent info platforms (IIS) should be outlined because the subsequent new release of data platforms (IS) constructed due to integration of AI and database (DB) applied sciences. IIS embrace wisdom that permits them to express clever habit, permits them to cooperate with clients and different platforms in challenge fixing, discovery, retrieval, and manipulation of knowledge and information. For any IIS to serve its objective, the data has to be on hand while it's wanted. which means the computing platforms used to shop information and approach the data, and the safety controls used to guard it has to be functioning accurately. This booklet covers the various above themes and it really is divided into 4 sections: category, Approximation and knowledge safety, wisdom administration, and alertness of IIS to scientific and track domains.

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Morgan Kaufmann, San Mateo (1993) 19. : On measures of entropy and information. In: 4th Berkely Symp. Math. Statist. Probability, vol. 1, pp. 547–561 (1960) 20. : Donn´ees d´es´equilibr´ees, entropie d´ecentr´ee et indice d’implication. , Gregori, P. ) Nouveaux apports th´eoriques a` l’analyse statistique implicative et applications. actes des 4´emes rencontres ASI4, Castellon de la Plana (Espana), Departament de Matematiques, Universitat Jaume I, Octobre 18-21, pp. 315–327 (2007) 21. : Machine learning in automated text categorization.

N − 1. , n): ≥ ≥ ≤ ≤ ≤ Bn P (Cl≥ t ) = P ( Cl t )–P ( Cl t ), Bn P (Cl t ) = P ( Cl t )–P ( Cl t ). , n. For every P ⊆ C, the quality of approximation of the ordinal classification Cl by a set of criteria P is defined as the ratio of the number of objects P -consistent with the dominance principle and the number of all the objects in U . Since the P -consistent objects are those which do not belong to any ≤ P -boundary BnP (Cl≥ t ), t = 2, . . , n, or BnP (Cl t ), t = 1, . . ,n−1 |U | BnP (Clt≤ ) .

Students of a college must obtain an overall evaluation on the basis of their achievements in Mathematics, Physics and Literature. The three subjects are clearly criteria (condition attributes) and the comprehensive evaluation is a decision attribute. For simplicity, the value sets of the criteria and of the decision attribute are the same, and they are composed of three values: bad, medium and good. The preference order of these values is obvious. Thus, there are three preference ordered decision classes, so the problem belongs to the category of ordinal classification.

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