Applications of Declarative Programming and Knowledge Management : 17th International Conference

This volume contains a selection of papers presented at the 17th International Conference on Applications of Declarative Programming and Knowledge M- agement INAP 2007 and the 21st Workshop on Logic Programming WLP 2007, which were held jointly in Wu ]rzburg, Germany, during October 4-6, 2007. Declarative programming is anadvancedparadigmforthe modelingandso- ing of complex problems. This speci?cation method has become more and more attractiveoverthelastyears, e.g., inthedomainsofdatabases, fortheprocessing of natural language, for the modeling and processing of combinatorial problems, and for establishing knowledge-based systems for the Web. The INAP conferences provide a forum for intensive discussions of appli- tions of important technologies around logic programming, constraint problem solving, and closely related advanced software. They comprehensively cover the impactof programmablelogic solversin the Internetsociety, its underlying te- nologies, and leading-edge applications in industry, commerce, government, and societal services. The WorkshopsonLogicProgrammingarethe annualmeeting of the Society for Logic Programming (GLP e.V.). They bring together researchers interested in logic programming, constraint programming, and related areas like databases and arti?cial intelligence. Previous workshops have been held in Germany, A- tria and Switzerland. The topics of the selected papers of this years joint conference concentrated on three currently important ?elds: constraint programming and constraint solving, databases and data mining, and declarative programming with logic languages. Duringthelastcoupleofyearsalotofresearchhasbeenconductedonthe- ageof declarativeprogrammingfor databases and data mining. Reasoning about knowledgewrappedinrules, databases, ortheWeballowsonetoexploreintere- ing hidden knowledge.Declarativetechniques for the transformation, deduction, induction, visualization, or querying of knowledge, or data mining techniques for exploring knowledge have the advantage of high transparency and better maintainability compared to procedural approaches.