Titlebook: Scalable Uncertainty Management; First International Henri Prade,V. S. Subrahmanian Conference proceedings 2007 Springer-Verlag Berlin Hei

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Terrace

Preferred Database Repairs Under Aggregate Constraints, is based on a transformation into an Integer Linear Programming (ILP) instance. Aggregate constraints are linear inequalities on aggregates retrieved from the input data. While strong constraints express mandatory conditions, weak constraints define conditions which are expected to be satisfied, ev

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amenity

Learning from Imprecise Granular Data Using Trapezoidal Fuzzy Set Representations,implementing many operations involving trapezoidal fuzzy sets. Attention is particularly brought to the simplification that the linearity of the trapezoid brings in that it often allows us to perform operations on only two level sets. We investigate the classic learning algorithm in the case when ou

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Refining Aggregation Functions for Improving Document Ranking in Information Retrieval,en documents because some information is lost in this aggregation. To cope with this problem, the paper presents an approach for ranking documents in IR, based on a refined vector-based ordering technique taken from multiple criteria analysis methods. Different vector representations of the retrieva

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Finding Most Probable Worlds of Probabilistic Logic Programs,brahmanian) and yet solve the problem exactly. However, the intractability results still make computational efficiency quite impossible. We therefore also develop several heuristics to solve the MPW problem and report extensive experimental results on the accuracy and efficiency of such heuristics.

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Learning Different User Profile Annotated Rules for Fuzzy Preference Top-k Querying,matic assignment of user model we design two algorithms, one for learning user preference on particular attribute and second for learning the combination function. Methods were integrated into a Fagin-like top-k querying system with some new heuristics and tested.