F. Sadri. Modeling Uncertainty in Databases. Proceedings of the Seventh IEEE International Conference on Data Engineering, April, 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... The underlying uncertainty formalisms in the proposed frameworks include probability theory [17, 18, 22, 23] fuzzy set theory [26, 30] multi valued logic [9, 10, 13, 15] possibilistic logic [6] evidence theory [21] and hybrid (i.e. a combination of numerical and non numerical) formalisms [17, 16, 24]. Examples 2.1 2.6 illustrate these frameworks informally. We do not enter into a debate of which form of uncertainty is the best. Rather, our contention is that di erent forms may be appropriate for di erent applications. Furthermore, di erent ways of manipulating uncertainty may be required ....

Sadri Fereidoon. Modeling uncertainty in databases. In Proc. 7th IEEE Intl. Conf. on Data Eng., pages 122-131, April 1991. 33

....extensions to the relational model. 9] Uncertainty (e.g. relevancy rankings) is injected into a structured data model and query language. Uncertainty, however, stems not only from integration. Because of the potential for conflicts, multi source querying inherently invokes uncertainty. [19, 18] uses a vector notation and an extended relational algebra to associate data sources with tuples in the relation. A probabilistic interpretation of the combination of source vectors produces an assessment of each associated tuple s reliability. Though the intuition behind attribution is similar, ....

Fereidoon Sadri. Modeling uncertainty in databases. In Proc of the 7th Intl Conf on Data Eng, pages 122--131, 1991.

....null values in databases and has about thirty years of history. Starting on early papers devoted to network (CODASYL) and relational databases many authors proposed extensions of capabilities of database systems for storing and querying irregular, uncertain or missing information. In particular, [LiSu90a, LiSu90b, Sadr91, VrLi91, VrLi93, WoLe90] propose various extensions of the relational algebra, CaPi87, Fuhr90, BGP90, BGP92] propose specialized probabilistic DBMSs, DrCh89, LeLo91,RKS89, RKS91, Yazi90] discuss nested relational algebras dealing with null values and [AKG91, INV91, Libk94] and a lot of other papers) propose methods of ....

F. Sadri. Modeling Uncertainty in Databases. Proc. 7th Conf. on Data Engineering, Kobe, Japan, 1991, pp.122-131.

....Debray and Ramakrishnan [10] 1 etc. are implication based, the first implication based framework for probabilistic deductive databases was proposed in [30] The idea behind implication based approach is to associate uncertainty with the facts as well as rules in a deductive database. Sadri [39, 40] in a number of papers developed a hybrid method called Information Source Tracking (IST) for modeling uncertainty in (relational) databases which combines symbolic and numeric approaches to modeling uncertainty. Lakshmanan and Sadri [31] pursue the deductive extension of this model using the ....

Sadri Fereidoon. Modeling uncertainty in databases. In Proc. 7th IEEE Intl. Conf. on Data Eng., pages 122--131, April 1991.

....but they do not imply specific problems or new quality for database management systems per se. Many authors, however, proposed extensions of ideological assumptions and generic capabilities of database systems for storing and querying uncertain or missing information. In particular, [LiSu90a, LiSu90b, Sadr91, VrLi91, VrLi93, WoLe90] propose various extensions of the relational algebra, CaPi87, Fuhr90, BGP90, BGP92] propose specialized probabilistic DBMSs. Moreover, DrCh89, LeLo91, RKS89, RKS91, Yazi90] discuss nested relational algebras dealing with null values and [AKG91, INV91, Libk94] and a lot of other papers) propose ....

F. Sadri. Modeling Uncertainty in Databases. Proc. 7th Conf. on Data Engineering, Kobe, Japan, 1991, pp.122--131.

.... as we must learn not only to cope with data of limited reliability, but to do so efficiently, with massive amounts of data [18] Information Source Tracking (IST) method has been developed recently for the modeling and manipulation of uncertain and inaccurate data in relational databases [14, 15, 16, 17]. In this paper we extend the IST method to deductive databases. First we concentrate on positive uncertain databases, i.e. IST based deductive databases with only positive literals in the heads and the bodies of the rules, and show that they enjoy a least model semantics, which coincides with the ....

F. Sadri "Modeling Uncertainty in Databases." Proceedings of the 1991 IEEE International Conference on Data Engineering, pp 122-131.

....u 2 )jt 1 u 1 2 r and t 2 u 2 2 sg Note that an implicit union operation takes place for source vectors in the selection, projection and union operations, while s disjunction and s negations of source vectors are used respectively for Cartesian product and set difference operations above. Sadri [5] proved that the operations are sound and complete. 3 Computing ff We take the view that the development of a satisfactory trust function is beyond the scope of this paper and is a research issue by itself. So, in this section we are merely interested in a function for trust calculation for ....

Sadri, F.; "Modeling Uncertainty in Databases"; IEEE 7th International Conference on Data Engineering; pp 122-131; 1991.

....definitions we make these notions precise. Definition 3.1 Let t = p a be a tuple in rf with regular attributes X and key K X. The function twin : rf 2 ra is a mapping that associates with every tuple 6 For a discussion on query processing using extended operators, readers are referred to [3, 4, 7, 8, 10]. t in facts of r, a set of archive tuples such that twin(t) ft 0 jt 0 2 r; t 0 [K] t[K]g. Let the neighborhood of t, denoted (t) be (t) ftg [ twin(t) 2 We now define the concept of similarity between two tuples in the context, called the neighbourhood, of their twins. Our idea of ....

....neighbourhood dependent similarity to avoid confusion with our concept of contexts of a relation. 5 Algorithm for Tuple Reliability Calculation We develop an outline of the reliability calculation algorithm for answer tuples in this section. This algorithm is based on the algorithms presented in [7, 8]. For simplicity, we will assume point credibility for agents instead of ranges in this paper. The basic idea is to calculate the combined credibility of an agent in all the contexts based on the notion of positive correlation and use the algorithm for basic IST. In basic IST [7] the agent ....

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Sadri, F.; "Modeling Uncertainty in Databases"; IEEE 7th International Conference on Data Engineering; pp 122-131; 1991.

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F. Sadri. Modeling Uncertainty in Databases. Proceedings of the Seventh IEEE International Conference on Data Engineering, April, 1991.

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Sadri, F. (1991). Modeling Uncertainty in Databases. In: Seventh International Conference on Data Engineering, pages 122--131. IEEE Computer Society, Los Angeles.

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