Poster Presentation: Xcerpt and XChange – Logic Programming Languages for Querying and Evolution on the Web

age Xcerpt and provides advanced, Web-specific capabilities, such as propagation of changes on the Web (change) and event-based communications between Web sites (exchange). Xcerpt: Querying Data on the Web Xcerpt is a declarative, rule-based query language for Web data (i.e. XML documents or semistructured databases) based on logic programming. An Xcerpt program contains at least one goal and some (maybe zero) rules. Rules and goals consist of query and construction patterns, called terms in analogy to other logic programming languages. Terms represent tree-like (or graph-like) structures. The children of a node may be either ordered (as in standard XML) or unordered (as is common in databases). Data terms are used to represent XML documents and the data items of a semistructured database. They are similar to ground functional programming expressions and logical atoms. A database is a (multi-)set of data terms (e.g. the Web). Query terms are patterns matched against Web resources

A Modular Logic Approach for Expressing Web Services in XML Applying Dynamic Rules in XML

RuleML is considered to be a markup language for the semantic web. It allows the enrichment of web ontologies by adding definitions of derived concepts and it enhances interoperability among different systems and tools by publishing rules in an XML format. Moreover the in-creasing demand for interfaces that enhance information sharing has given rise to XML doc-uments that include embedded calls to web services. In this paper we propose a variation of RuleML that is based on modular logic programming. Our approach is based in a two level architecture. In the first level a modular logic language, called M-log, is presented. This lan-guage encompasses several mechanisms for invoking web services. In the second level we ex-ploit the semantics of M-log to present a variation of RuleML with rich modeling capabilities. Formal foundations for this variation are given through direct translation to M-log semantics.Knowledge Management, XML, Modular Logic Programming, E-Services

Logic Programs with Compiled Preferences

We describe an approach for compiling preferences into logic programs under the answer set semantics. An ordered logic program is an extended logic program in which rules are named by unique terms, and in which preferences among rules are given by a set of dedicated atoms. An ordered logic program is transformed into a second, regular, extended logic program wherein the preferences are respected, in that the answer sets obtained in the transformed theory correspond with the preferred answer sets of the original theory. Our approach allows both the specification of static orderings (as found in most previous work), in which preferences are external to a logic program, as well as orderings on sets of rules. In large part then, we are interested in describing a general methodology for uniformly incorporating preference information in a logic program. Since the result of our translation is an extended logic program, we can make use of existing implementations, such as dlv and smodels. To this end, we have developed a compiler, available on the web, as a front-end for these programming systems

Building Rules on Top of Ontologies for the Semantic Web with Inductive Logic Programming

Building rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim an ad-hoc mark-up language for this layer is currently under discussion. It is intended to follow the tradition of hybrid knowledge representation and reasoning systems such as $\mathcal{AL}$-log that integrates the description logic $\mathcal{ALC}$ and the function-free Horn clausal language \textsc{Datalog}. In this paper we consider the problem of automating the acquisition of these rules for the Semantic Web. We propose a general framework for rule induction that adopts the methodological apparatus of Inductive Logic Programming and relies on the expressive and deductive power of $\mathcal{AL}$-log. The framework is valid whatever the scope of induction (description vs. prediction) is. Yet, for illustrative purposes, we also discuss an instantiation of the framework which aims at description and turns out to be useful in Ontology Refinement. Keywords: Inductive Logic Programming, Hybrid Knowledge Representation and Reasoning Systems, Ontologies, Semantic Web. Note: To appear in Theory and Practice of Logic Programming (TPLP)Comment: 30 pages, 6 figure

Development of a Logic Layer in the Semantic Web: Research Issues

The ontology layer of the semantic web is now mature enough (i.e. standards like RDF, RDFs, OWL, OWL 2) and the next step is to work on a logic layer for the development of advanced reasoning capabilities for knowledge extraction and efficient decision making. Adding logic to the web means using rules to make inferences. Rules are a means of expressing business processes, policies, contracts etc but most of the studies have focused on the use of monotonic logics in layered development of the semantic web which provides no mechanism for representing or handling incomplete or contradictory information respectively. This paper discusses argumentation, semantic web and defeasible logic programming with their distinct features and identifies the different research issues that need to be addressed in order to realize defeasible argumentative reasoning in the semantic web applications