Answer Set Programming for the Semantic Web

The World Wide Web (WWW) is currently by far the largest and most frequently-accessed data repository available. However, most of the documents an the Web are only suitable for direct use by human consumers, but are not accessible for automated information processing.Consequently, a large body of processes cannot be fully automated and there is no common way of expressing and manipulating information and knowledge about Web data. This shortcoming is clearly recognized by the scientific community and there is currently extensive work under way to build the foundations of the next-generation Web (the so-called "Semantic Web") in order to provide reasoning support over Web content. Current efforts in this direction focus an terminological reasoning only, expressing tasks like classification and instance checking. However, there is a need for other, more flexible forms of reasoning. The goal of this project is to research methods for providing advanced reasoning services in tbe context of the Semantic Web, using declarative knowledge representation and reasoning teclniques. In particular, we shall investigate the use of logic programming under the answer set semantics for realizing languages and tools which extend the capabilities of current approaches, in order to support (reasoning aware querying) of the Web. Special attention will be given to the study of suitable models and algorithms for dealing with incomplete and preference infonnation. Furthermore, we will develop modules to support advanced reasoning tasks for particular applications in the context of policy specification and personalized information systems.