Scalable Uncertainty Management

First International Conference, SUM 2007, Washington, DC, USA, October 10-12, 2007, Proceedings

Häftad, Engelska, 2007

Av Henri Prade, V.S. Subrahmanian, V. S. Subrahmanian

729 kr

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This book constitutes the refereed proceedings of the First International Conference on Scalable Uncertainty Management, SUM 2007, held in Washington, DC, USA, in October 2007. The 20 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers address artificial intelligence researchers, database researchers and practitioners.

Produktinformation

Utgivningsdatum2007-09-27
Mått155 x 235 x 16 mm
Vikt446 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Artificial Intelligence
Antal sidor280
Upplaga2007
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783540754077

Tillhör följande kategorier

Företagsekonomi inom Ekonomi och ledarskap
Systemvetenskap och AI inom Data och it
Artificiell intelligens inom Data och it

Probabilistic Planning in Hybrid Probabilistic Logic Programs.- Top-k Retrieval in Description Logic Programs Under Vagueness for the Semantic Web.- A Fuzzy Set-Based Approach to Temporal Databases.- Finding Most Probable Worlds of Probabilistic Logic Programs.- Managing Uncertainty in Schema Matcher Ensembles.- The Consistency Extractor System: Querying Inconsistent Databases Using Answer Set Programs.- Incomplete Statistical Information Fusion and Its Application to Clinical Trials Data.- Quality Measures in Uncertain Data Management.- Learning Different User Profile Annotated Rules for Fuzzy Preference Top-k Querying.- Composable Markov Building Blocks.- Tractable Probabilistic Description Logic Programs.- Valued Hesitation in Intervals Comparison.- Aggregates in Generalized Temporally Indeterminate Databases.- An Indexing Technique for Fuzzy Numerical Data.- Combining Uncertain Outputs from Multiple Ontology Matchers.- Preferred Database Repairs Under Aggregate Constraints.- Consistent Data Integration in P2P Deductive Databases.- Learning from Imprecise Granular Data Using Trapezoidal Fuzzy Set Representations.- Refining Aggregation Functions for Improving Document Ranking in Information Retrieval.- A Qualitative Bipolar Argumentative View of Trust.