Download e-book for kindle: Advances in Probabilistic Databases for Uncertain by John Grant, Francesco Parisi (auth.), Zongmin Ma, Li Yan

By John Grant, Francesco Parisi (auth.), Zongmin Ma, Li Yan (eds.)

ISBN-10: 3642375081

ISBN-13: 9783642375088

ISBN-10: 364237509X

ISBN-13: 9783642375095

This publication covers a fast-growing subject in nice intensity and makes a speciality of the applied sciences and purposes of probabilistic info administration. It goals to supply a unmarried account of present reports in probabilistic facts administration. the target of the publication is to supply the state-of-the-art details to researchers, practitioners, and graduate scholars of knowledge expertise of clever details processing, and whilst serving the knowledge know-how specialist confronted with non-traditional functions that make the appliance of traditional methods tough or impossible.

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We say that the px-space X is finite if X has a finite support; otherwise, X is infinite. When there is no risk of ambiguity, we may abuse our notation and identify a pxspace X by the random variable that gets a document chosen according to the distribution of X . So, for example, if X = (D, p) and d is a document, then Pr (X = d) (in words, the probability that X is equal to d) is p(d) if d ∈ D, and 0 otherwise. 3 p-Documents A px-space is encoded by means of a compact representation. Later in this chapter, we will discuss the plethora of representation models proposed and studied in the literature.

Formally, let e be a complex and stochastic event, which corresponds to a virtual object ov and is described by a group of objects {o1, o2, …, ok}. Here o1, o2, …, ok have the same object identifier. Let the probability measure of object oi (1 ≤ i ≤ k) be oi (pe). Then we have i = 1, 2, …, k oi (pe) ≤ 1. The probability measure associated with an object is a crisp one expressed by a precise value when it is definitely known. Also it is possible that the probability measure associated with an object is fuzzily known.

Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems. ACM Transactions on Database Systems 13(2), 129–166 (1988) 25. : Fuzzy relational algebra for possibility-distribution-fuzzyrelational model of fuzzy data. Journal of Intelligent Information Systems 3(1), 7–27 (1994) 26. : Algebraic operations in fuzzy object-oriented databases. 1007/s10796-012-9359-8 27. : Efficient processing of nested fuzzy SQL queries in a fuzzy database. IEEE Transactions on Knowledge and Data Engineering 13(6), 884–901 (2001) 28.

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Advances in Probabilistic Databases for Uncertain Information Management by John Grant, Francesco Parisi (auth.), Zongmin Ma, Li Yan (eds.)


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