LEADER 05902nam 2200625 a 450 001 9910483706603321 005 20200520144314.0 010 $a1-280-38928-1 010 $a9786613567208 010 $a3-642-15951-6 024 7 $a10.1007/978-3-642-15951-0 035 $a(CKB)2670000000045126 035 $a(SSID)ssj0000446755 035 $a(PQKBManifestationID)11298852 035 $a(PQKBTitleCode)TC0000446755 035 $a(PQKBWorkID)10496421 035 $a(PQKB)10893685 035 $a(DE-He213)978-3-642-15951-0 035 $a(MiAaPQ)EBC3065875 035 $a(PPN)149024932 035 $a(EXLCZ)992670000000045126 100 $a20100812d2010 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aScalable uncertainty management $e4th International Conference, SUM 2010, Toulouse, France, September 27-29, 2010 : proceedings /$fAmol Deshpande, Anthony Hunter (eds.) 205 $a1st ed. 2010. 210 $aBerlin ;$aNew York $cSpringer$d2010 215 $a1 online resource (XI, 389 p. 79 illus.) 225 1 $aLNCS sublibrary. SL 7, Artificial intelligence 225 1 $aLecture notes in computer science. Lecture notes in artificial intelligence,$x0302-9743 ;$v6379 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-15950-8 320 $aIncludes bibliographical references and index. 327 $aInvited Talks -- Markov Chain Monte Carlo and Databases -- Answer Set Programming, the Solving Paradigm for Knowledge Representation and Reasoning -- Discussant Contributions -- Graphical and Logical-Based Representations of Uncertain Information in a Possibility Theory Framework -- Probabilistic Data: A Tiny Survey -- The Role of Epistemic Uncertainty in Risk Analysis -- Uncertainty in Clustering and Classification -- Information Fusion -- Use of the Domination Property for Interval Valued Digital Signal Processing -- Regular Contributions -- Managing Lineage and Uncertainty under a Data Exchange Setting -- A Formal Analysis of Logic-Based Argumentation Systems -- Handling Inconsistency with Preference-Based Argumentation -- A Possibility Theory-Oriented Discussion of Conceptual Pattern Structures -- DK-BKM: Decremental K Belief K-Modes Method -- On the Use of Fuzzy Cardinalities for Reducing Plethoric Answers to Fuzzy Queries -- From Bayesian Classifiers to Possibilistic Classifiers for Numerical Data -- Plausibility of Information Reported by Successive Sources -- Combining Semantic Web Search with the Power of Inductive Reasoning -- Evaluating Trust from Past Assessments with Imprecise Probabilities: Comparing Two Approaches -- Range-Consistent Answers of Aggregate Queries under Aggregate Constraints -- Characterization, Propagation and Analysis of Aleatory and Epistemic Uncertainty in the 2008 Performance Assessment for the Proposed Repository for High-Level Radioactive Waste at Yucca Mountain, Nevada -- Comparing Evidential Graphical Models for Imprecise Reliability -- Imprecise Bipolar Belief Measures Based on Partial Knowledge from Agent Dialogues -- Kriging with Ill-Known Variogram and Data -- Event Modelling and Reasoning with Uncertain Information for Distributed Sensor Networks -- Uncertainty in Decision Tree Classifiers -- Efficient Policy-Based Inconsistency Management in Relational Knowledge Bases -- Modelling Probabilistic Inference Networks and Classification in Probabilistic Datalog -- Handling Dirty Databases: From User Warning to Data Cleaning ? Towards an Interactive Approach -- Disjunctive Fuzzy Logic Programs with Fuzzy Answer Set Semantics -- Cost-Based Query Answering in Action Probabilistic Logic Programs -- Clustering Fuzzy Data Using the Fuzzy EM Algorithm -- Combining Multi-resolution Evidence for Georeferencing Flickr Images -- A Structure-Based Similarity Spreading Approach for Ontology Matching -- Risk Modeling for Decision Support. 330 $aManaging uncertainty and inconsistency has been extensively explored in - ti?cial Intelligence over a number of years. Now with the advent of massive amounts of data and knowledge from distributed heterogeneous,and potentially con?icting, sources, there is interest in developing and applying formalisms for uncertainty andinconsistency widelyin systems that need to better managethis data and knowledge. The annual International Conference on Scalable Uncertainty Management (SUM) has grown out of this wide-ranging interest in managing uncertainty and inconsistency in databases, the Web, the Semantic Web, and AI. It aims at bringing together all those interested in the management of large volumes of uncertainty and inconsistency, irrespective of whether they are in databases,the Web, the Semantic Web, or in AI, as well as in other areas such as information retrieval, risk analysis, and computer vision, where signi?cant computational - forts are needed. After a promising First International Conference on Scalable Uncertainty Management was held in Washington DC, USA in 2007, the c- ference series has been successfully held in Napoli, Italy, in 2008, and again in Washington DC, USA, in 2009. 410 0$aLecture notes in computer science.$pLecture notes in artificial intelligence. 410 0$aLecture notes in computer science.$pLecture notes in artificial intelligence ;$v6379. 606 $aUncertainty (Information theory)$vCongresses 606 $aArtificial intelligence$vCongresses 615 0$aUncertainty (Information theory) 615 0$aArtificial intelligence 676 $a003/.54 701 $aDeshpande$b Amol$0856334 701 $aHunter$b Anthony$0734522 712 12$aSUM (Conference) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483706603321 996 $aScalable uncertainty management$94195656 997 $aUNINA