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020 _a9783642359750
_9978-3-642-35975-0
024 7 _a10.1007/978-3-642-35975-0
_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 _aUncertainty Reasoning for the Semantic Web II
_h[electronic resource] :
_bInternational Workshops URSW 2008-2010 Held at ISWC and UniDL 2010 Held at FLoC, Revised Selected Papers /
_cedited by Fernando Bobillo, Paulo C. G. Costa, Claudia d’Amato, Nicola Fanizzi, Kathryn B. Laskey, Kenneth J. Laskey, Thomas Lukasiewicz, Matthias Nickles, Michael Pool.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXVI, 331 p. 72 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 ;
_v7123
505 0 _aPR-OWL 2.0 – Bridging the Gap to OWL Semantics.- Probabilistic Ontology and Knowledge Fusion for Procurement Fraud Detection in Brazil -- Understanding a Probabilistic Description Logic via Connections to First-Order Logic of Probability.- Pronto: A Practical Probabilistic Description Logic Reasoner.- Instance-Based Non-standard Inferences in EL with Subjective Probabilities.- Finite Fuzzy Description Logics and Crisp Representations.- Reasoning in Fuzzy OWL 2 with DeLorean.- Dealing with Contradictory Evidence Using Fuzzy Trust in Semantic Web Data.- Storing and Querying Fuzzy Knowledge in the Semantic Web Using FiRE.- Transforming Fuzzy Description Logic ALCFL into Classical Description Logic ALCH.- A Fuzzy Logic-Based Approach to Uncertainty Treatment in the Rule Interchange Format: From Encoding to Extension. PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation Using Probabilistic Methods.- Semantic Web Search and Inductive Reasoning.- Ontology Enhancement through Inductive Decision Trees.- Assertion Prediction with Ontologies through Evidence Combination.- Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations.- Efficient Trust-Based Approximate SPARQL Querying of the Web of Linked Data -- Probabilistic Ontology and Knowledge Fusion for Procurement Fraud Detection in Brazil -- Understanding a Probabilistic Description Logic via Connections to First-Order Logic of Probability.- Pronto: A Practical Probabilistic Description Logic Reasoner.- Instance-Based Non-standard Inferences in EL with Subjective Probabilities.- Finite Fuzzy Description Logics and Crisp Representations.- Reasoning in Fuzzy OWL 2 with DeLorean.- Dealing with Contradictory Evidence Using Fuzzy Trust in Semantic Web Data.- Storing and Querying Fuzzy Knowledge in the Semantic Web Using FiRE.- Transforming Fuzzy Description Logic ALCFL into Classical Description Logic ALCH.- A Fuzzy Logic-Based Approach to Uncertainty Treatment in the Rule Interchange Format: From Encoding to Extension.- PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation Using Probabilistic Methods.- Semantic Web Search and Inductive Reasoning.- Ontology Enhancement through Inductive Decision Trees.- Assertion Prediction with Ontologies through Evidence Combination.- Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations.- Efficient Trust-Based Approximate SPARQL Querying of the Web of Linked Data.
520 _aThis book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2008, 2009, and 2010 or presented at the first international Workshop on Uncertainty in Description Logics (UniDL), held at the Federated Logic Conference (FLoC) in 2010. The 17 papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.
650 0 _aComputer science.
650 0 _aMathematical logic.
650 0 _aMathematical statistics.
650 0 _aData mining.
650 0 _aInformation storage and retrieval.
650 0 _aUser interfaces (Computer systems).
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aMathematical Logic and Formal Languages.
650 2 4 _aProbability and Statistics in Computer Science.
700 1 _aBobillo, Fernando.
_eeditor.
700 1 _aCosta, Paulo C. G.
_eeditor.
700 1 _ad’Amato, Claudia.
_eeditor.
700 1 _aFanizzi, Nicola.
_eeditor.
700 1 _aLaskey, Kathryn B.
_eeditor.
700 1 _aLaskey, Kenneth J.
_eeditor.
700 1 _aLukasiewicz, Thomas.
_eeditor.
700 1 _aNickles, Matthias.
_eeditor.
700 1 _aPool, Michael.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642359743
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v7123
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-35975-0
912 _aZDB-2-SCS
912 _aZDB-2-LNC
942 _2Dewey Decimal Classification
_ceBooks
999 _c46698
_d46698