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Uncertainty Reasoning for the Semantic Web II

International Workshops URSW 2008-2010 Held at ISWC and UniDL 2010 Held at Floc, Revised Selected Papers

  • Conference proceedings
  • © 2013

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Editors:
  1. Fernando Bobillo

    1. Department of Computer Science and Systems Engineering, University of Zaragoza, Zaragoza, Spain

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  2. Paulo C. G. Costa

    1. Department of Systems Engineering and Operations Research, George Mason University, Fairfax, USA

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  3. Claudia d’Amato

    1. Dipatimento di Informatica, Università degli Studi di Bari, Bari, Italy

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  4. Nicola Fanizzi

    1. Dipatimento di Informatica and CILA, Università degli Studi di Bari, Bari, Italy

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  5. Kathryn B. Laskey

    1. Department of Systems Engineering and Operations Research, George Mason University, Fairfax, USA

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  6. Kenneth J. Laskey

    1. MIRTE Corporation, McLean, USA

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  7. Thomas Lukasiewicz

    1. Department of Computer Science, University of Oxford, Oxford, UK

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  8. Matthias Nickles

    1. Technische Universität München, Garching, Germany

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  9. Michael Pool

    1. Goldman Sachs, Jersey City, USA

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  • High quality selected papers
  • Unique visibility
  • State of the art research

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7123)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: UniDL 2010, URSW 2008. URSW 2009. URSW 2010.

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Table of contents (17 papers)

  1. Front Matter

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  2. Probabilistic and Dempster-Shafer Models

    1. PR-OWL 2.0 – Bridging the Gap to OWL Semantics

      • Rommel N. Carvalho, Kathryn B. Laskey, Paulo C. G. Costa
      Pages 1-18

    2. Probabilistic Ontology and Knowledge Fusion for Procurement Fraud Detection in Brazil

      • Rommel N. Carvalho, Shou Matsumoto, Kathryn B. Laskey, Paulo C. G. Costa, Marcelo Ladeira, Laécio L. Santos
      Pages 19-40

    3. Understanding a Probabilistic Description Logic via Connections to First-Order Logic of Probability

      • Pavel Klinov, Bijan Parsia
      Pages 41-58

    4. Pronto: A Practical Probabilistic Description Logic Reasoner

      • Pavel Klinov, Bijan Parsia
      Pages 59-79

    5. Instance-Based Non-standard Inferences in \(\mathcal{EL}\) with Subjective Probabilities

      • Rafael Peñaloza, Anni-Yasmin Turhan
      Pages 80-98

  3. Fuzzy and Possibilistic Models

    1. Finite Fuzzy Description Logics and Crisp Representations

      • Fernando Bobillo, Umberto Straccia
      Pages 99-118

    2. Reasoning in Fuzzy OWL 2 with DeLorean

      • Fernando Bobillo, Miguel Delgado, Juan Gómez-Romero
      Pages 119-138

    3. Dealing with Contradictory Evidence Using Fuzzy Trust in Semantic Web Data

      • Miklos Nagy, Maria Vargas-Vera
      Pages 139-157

    4. Storing and Querying Fuzzy Knowledge in the Semantic Web Using FiRE

      • Nikolaos Simou, Giorgos Stoilos, Giorgos Stamou
      Pages 158-176

    5. Transforming Fuzzy Description Logic \(\mathcal{ALC}_\mathcal{FL}\) into Classical Description Logic \(\mathcal{ALCH}\)

      • Yining Wu
      Pages 177-196

    6. A Fuzzy Logic-Based Approach to Uncertainty Treatment in the Rule Interchange Format: From Encoding to Extension

      • Jidi Zhao, Harold Boley, Jing Dong
      Pages 197-216

  4. Inductive Reasoning and Machine Learning

    1. PrOntoLearn: Unsupervised Lexico-Semantic Ontology Generation Using Probabilistic Methods

      • Saminda Abeyruwan, Ubbo Visser, Vance Lemmon, Stephan Schürer
      Pages 217-236

    2. Semantic Web Search and Inductive Reasoning

      • Claudia d’Amato, Nicola Fanizzi, Bettina Fazzinga, Georg Gottlob, Thomas Lukasiewicz
      Pages 237-261

    3. Ontology Enhancement through Inductive Decision Trees

      • Bart Gajderowicz, Alireza Sadeghian, Mikhail Soutchanski
      Pages 262-281

    4. Assertion Prediction with Ontologies through Evidence Combination

      • Giuseppe Rizzo, Claudia d’Amato, Nicola Fanizzi, Floriana Esposito
      Pages 282-299

  5. Hybrid Approaches

    1. Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations

      • Claudia d’Amato, Nicola Fanizzi, Floriana Esposito, Thomas Lukasiewicz
      Pages 300-314

    2. Efficient Trust-Based Approximate SPARQL Querying of the Web of Linked Data

      • Kuldeep B. R. Reddy, P. Sreenivasa Kumar
      Pages 315-330

  6. Back Matter

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Keywords

About this book

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.

Editors and Affiliations

  • Department of Computer Science and Systems Engineering, University of Zaragoza, Zaragoza, Spain

    Fernando Bobillo

  • Department of Systems Engineering and Operations Research, George Mason University, Fairfax, USA

    Paulo C. G. Costa, Kathryn B. Laskey

  • Dipatimento di Informatica, Università degli Studi di Bari, Bari, Italy

    Claudia d’Amato

  • Dipatimento di Informatica and CILA, Università degli Studi di Bari, Bari, Italy

    Nicola Fanizzi

  • MIRTE Corporation, McLean, USA

    Kenneth J. Laskey

  • Department of Computer Science, University of Oxford, Oxford, UK

    Thomas Lukasiewicz

  • Technische Universität München, Garching, Germany

    Matthias Nickles

  • Goldman Sachs, Jersey City, USA

    Michael Pool

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