ISWC 2005-2007: URSW

Probabilistic and Dempster-Shafer Models

• Pedro Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla:
  Just Add Weights: Markov Logic for the Semantic Web. 1-25
  
• David Poole, Clinton Smyth, Rita Sharma:
  Semantic Science: Ontologies, Data and Probabilistic Theories. 26-40
  
• Paolo Besana, Dave Robertson:
  Probabilistic Dialogue Models for Dynamic Ontology Mapping. 41-51
  
• Andrea Calì, Thomas Lukasiewicz:
  An Approach to Probabilistic Data Integration for the Semantic Web. 52-65
  
• Andrea Calì, Thomas Lukasiewicz, Livia Predoiu, Heiner Stuckenschmidt:
  Rule-Based Approaches for Representing Probabilistic Ontology Mappings. 66-87
  
• Paulo Cesar G. da Costa, Kathryn B. Laskey, Kenneth J. Laskey:
  PR-OWL: A Bayesian Ontology Language for the Semantic Web. 88-107
  
• Francisco Martín-Recuerda, Dave Robertson:
  Discovery and Uncertainty in Semantic Web Services. 108-123
  
• Matthias Nickles, Ruth Cobos:
  An Approach to Description Logic with Support for Propositional Attitudes and Belief Fusion. 124-142
  
• Andriy Nikolov, Victoria S. Uren, Enrico Motta, Anne N. De Roeck:
  Using the Dempster-Shafer Theory of Evidence to Resolve ABox Inconsistencies. 143-160
  
• Hai-Tao Zheng, Bo-Yeong Kang, Hong-Gee Kim:
  An Ontology-Based Bayesian Network Approach for Representing Uncertainty in Clinical Practice Guidelines. 161-173
  

Fuzzy and Possibilistic Models

• Fernando Bobillo, Miguel Delgado, Juan Gómez-Romero:
  A Crisp Representation for Fuzzy with Fuzzy Nominals and General Concept Inclusions. 174-188
  
• Fernando Bobillo, Miguel Delgado, Juan Gómez-Romero:
  Optimizing the Crisp Representation of the Fuzzy Description Logic. 189-206
  
• Alan Eckhardt, Tomás Horváth, Dusan Maruscák, Robert Novotny, Peter Vojtás:
  Uncertainty Issues and Algorithms in Automating Process Connecting Web and User. 207-223
  
• Trevor P. Martin, Yun Shen, Ben Azvine:
  Granular Association Rules for Multiple Taxonomies: A Mass Assignment Approach. 224-243
  
• Mauro Mazzieri, Aldo Franco Dragoni:
  A Fuzzy Semantics for the Resource Description Framework. 244-261
  
• Giorgos Stoilos, Giorgos B. Stamou, Jeff Z. Pan, Nikos Simou, Vassilis Tzouvaras:
  Reasoning with the Fuzzy Description Logic f-: Theory, Practice and Applications. 262-281
  

Inductive Reasoning and Machine Learning

• Volker Tresp, Markus Bundschus, Achim Rettinger, Yi Huang:
  Towards Machine Learning on the Semantic Web. 282-314
  
• Joaquín Borrego-Díaz, Antonia M. Chávez-González:
  Using Cognitive Entropy to Manage Uncertain Concepts in Formal Ontologies. 315-329
  
• Claudia d'Amato, Nicola Fanizzi, Floriana Esposito:
  Analogical Reasoning in Description Logics. 330-347
  
• Nicola Fanizzi, Claudia d'Amato, Floriana Esposito:
  Approximate Measures of Semantic Dissimilarity under Uncertainty. 348-365
  
• Peter Haase, Johanna Völker:
  Ontology Learning and Reasoning - Dealing with Uncertainty and Inconsistency. 366-384
  

Hybrid Approaches

• Volker Haarslev, Hsueh-Ieng Pai, Nematollaah Shiri:
  Uncertainty Reasoning for Ontologies with General TBoxes in Description Logic. 385-402
  

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