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|a 9783642359750
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|a 10.1007/978-3-642-35975-0
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|a Uncertainty Reasoning for the Semantic Web II
|h [electronic resource] :
|b International Workshops URSW 2008-2010 Held at ISWC and UniDL 2010 Held at FLoC, Revised Selected Papers /
|c edited by Fernando Bobillo, Paulo C. G. Costa, Claudia d’Amato, Nicola Fanizzi, Kathryn B. Laskey, Kenneth J. Laskey, Thomas Lukasiewicz, Matthias Nickles, Michael Pool.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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|a XVI, 331 p. 72 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 7123
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|a PR-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.
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|a This 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.
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| 650 |
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0 |
|a Computer science.
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| 650 |
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0 |
|a Mathematical logic.
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| 650 |
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0 |
|a Mathematical statistics.
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| 650 |
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0 |
|a Data mining.
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| 650 |
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0 |
|a Information storage and retrieval.
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| 650 |
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0 |
|a User interfaces (Computer systems).
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| 650 |
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0 |
|a Artificial intelligence.
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| 650 |
1 |
4 |
|a Computer Science.
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| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
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| 650 |
2 |
4 |
|a Data Mining and Knowledge Discovery.
|
| 650 |
2 |
4 |
|a Information Storage and Retrieval.
|
| 650 |
2 |
4 |
|a User Interfaces and Human Computer Interaction.
|
| 650 |
2 |
4 |
|a Mathematical Logic and Formal Languages.
|
| 650 |
2 |
4 |
|a Probability and Statistics in Computer Science.
|
| 700 |
1 |
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|a Bobillo, Fernando.
|e editor.
|
| 700 |
1 |
|
|a Costa, Paulo C. G.
|e editor.
|
| 700 |
1 |
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|a d’Amato, Claudia.
|e editor.
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| 700 |
1 |
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|a Fanizzi, Nicola.
|e editor.
|
| 700 |
1 |
|
|a Laskey, Kathryn B.
|e editor.
|
| 700 |
1 |
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|a Laskey, Kenneth J.
|e editor.
|
| 700 |
1 |
|
|a Lukasiewicz, Thomas.
|e editor.
|
| 700 |
1 |
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|a Nickles, Matthias.
|e editor.
|
| 700 |
1 |
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|a Pool, Michael.
|e editor.
|
| 710 |
2 |
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|a SpringerLink (Online service)
|
| 773 |
0 |
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|t Springer eBooks
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783642359743
|
| 830 |
|
0 |
|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 7123
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-642-35975-0
|z Full Text via HEAL-Link
|
| 912 |
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|a ZDB-2-SCS
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| 912 |
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|a ZDB-2-LNC
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| 950 |
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|a Computer Science (Springer-11645)
|
