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001 978-3-642-15951-0
003 DE-He213
005 20160624102149.0
007 cr nn 008mamaa
008 100917s2010 gw | s |||| 0|eng d
020 _a9783642159510
_9978-3-642-15951-0
024 7 _a10.1007/978-3-642-15951-0
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aScalable Uncertainty Management
_h[electronic resource] :
_b4th International Conference, SUM 2010, Toulouse, France, September 27-29, 2010. Proceedings /
_cedited by Amol Deshpande, Anthony Hunter.
260 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _aXI, 389p. 79 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v6379
505 0 _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.
520 _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.
650 0 _aComputer science.
650 0 _aComputer Communication Networks.
650 0 _aDatabase management.
650 0 _aData mining.
650 0 _aInformation storage and retrieval systems.
650 0 _aInformation systems.
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aInformation Systems Applications (incl.Internet).
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aComputer Communication Networks.
650 2 4 _aDatabase Management.
650 2 4 _aData Mining and Knowledge Discovery.
700 1 _aDeshpande, Amol.
_eeditor.
700 1 _aHunter, Anthony.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642159503
786 _dSpringer
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v6379
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-15951-0
942 _2EBK9322
_cEBK
999 _c38616
_d38616