Important Dates
Call for Papers
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Invited Talks
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Accepted Papers
Author Instructions
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Invited Talks

Invited talks will be given by:

Jürgen Dix (University of Manchester, UK)
Tentative title: Computational Logic and Multi-Agency

Georg Gottlob (Vienna University of Technology, Austria)
Title: Declarative Information Extraction, Web Crawling and Recursive Wrapping with Lixto
Lixto is a system and method for the visual and interactive generation of wrappers for Web pages under the supervision of a human developer, for automatically extracting information from Web pages using such wrappers, and for translating the extracted content into XML. In this talk, we describe some advanced features of Lixto, such as disjunctive pattern definitions, specialisation rules, and Lixto's capability of collecting and aggregating information from several linked Web pages. We illustrate these features with significant examples from the commercial domain.
This will be a mixture between an invited talk and a system demo and will be given in conjunction with the system session.

Phokion Kolaitis (University of California at Santa Cruz, USA)
Title: On the Complexity of Model Checking and Inference in Minimal Models
Every logical formalism gives rise to two fundamental algorithmic problems: model checking and inference. In propositional logic, the model checking problem is polynomial-time solvable, while the inference problem is coNP-complete. In propositional circumscription, however, these problems have higher computational complexity, namely the model checking problem is coNP-complete, while the inference problem is complete for the second level of the polynomial hierarchy PH.
In this talk, we survey recent results on the computational complexity of restricted cases of these problems in the context of Schaefer's framework of generalized satisfiability problems. These results establish dichotomies in the complexity of the model checking problem and the inference problem for propositional circumscription. They yield a complete classification of the ``hard" and the ``easier" cases of these problems and also provide efficiently checkable criteria that tell apart the ``hard" cases from the ``easier" ones. This is joint work with Lefteris M. Kirousis of the University of Patras.

Maurizio Lenzerini (Università di Roma "La Sapienza", Italy)
Title: Data Integration Needs Reasoning
Data integration is the problem of combining the data residing at different sources, and providing a unified view of these data, called global schema, which can be queried by the user. The interest in this kind of systems has been continuously growing in the last years. However, the design of a data integration system is a very complex task, and several issues remains open, including how to express the relation between the global schema and the sources, and how to process queries expressed on the global schema. In this talk, we deal with these two problems, by presenting a logical framework for data integration, and by discussing the various choices for both the specification of a data integration system, and the design of query answering methods. Also, we elaborate on the observation that, in real world scenarios, the case of mutually inconsistent local databases will be very common, and we present the basic ideas in order to extend the integration framework with suitable nonmonotonic reasoning features for dealing with this case.

Chiaki Sakama (Wakayama University, Japan)
Tentative title: Nonmonotonic Inductive Logic Programming
Nonmonotonic logic programming (NMLP) and inductive logic programming (ILP) are two important extensions of logic programming. The former aims at representing incomplete knowledge and reasoning with commonsense, while the latter targets the problem of inductive construction of a general theory from examples and background knowledge. NMLP and ILP thus have seemingly different motivations and goals, but they have much in common in the background of problems, and techniques developed in each field are related to one another. In this talk, I present techniques for combining these two fields of logic programming in the context of nonmonotonic inductive logic programming (NMILP). I review recent results and problems to realize NMILP.