Semantic Web Languages and Semantic Web Services as Application Areas for Answer Set Programming

In the Semantic Web and Semantic Web Services areas there are still unclear issues concerning an appropriate language. Answer Set Programming and ASP engines can be particularly interesting for Ontological Reasoning, especially in the light of ongoing discussions of non-Monotonic extensions for Ontology Languages. Previously, the main concern of discussions was around OWL and Description Logics. Recently many extensions and suggestions for Rule Languages and Semantic Web Languages pop up, particularly in the the context of Semantic Web Services, which involve the meta-data description of Services instaead of static data on the Web only. These lanuages involve SWRL, WSML, SWSL-Rules, etc. I want to give an outline of languages, challenges and initiatives in this area and where I think Answer Set Programming research can hook in. (30min)

Loop Formulas for Description Logic Programs

Description Logic Programs (dl-programs) proposed by Eiter et al. constitute an elegant yet powerful formalism for the integration of answer set programming with description logics, for the Semantic Web. In this paper, we generalize the notions of completion and loop formulas of logic programs to description logic programs and show that the answer sets of a dl-program can be precisely captured by the models of its completion and loop formulas. Furthermore, we propose a new, alternative semantics for dl-programs, called the {\em canonical answer set semantics}, which is defined by the models of completion that satisfy what are called canonical loop formulas. A desirable property of canonical answer sets is that they are free of circular justifications. Some properties of canonical answer sets are also explored.Comment: 29 pages, 1 figures (in pdf), a short version appeared in ICLP'1

Entity set expansion from the Web via ASP

Knowledge on the Web in a large part is stored in various semantic resources that formalize, represent and organize it differently. Combining information from several sources can improve results of tasks such as recognizing similarities among objects. In this paper, we propose a logic-based method for the problem of entity set expansion (ESE), i.e. extending a list of named entities given a set of seeds. This problem has relevant applications in the Information Extraction domain, specifically in automatic lexicon generation for dictionary-based annotating tools. Contrary to typical approaches in natural languages processing, based on co-occurrence statistics of words, we determine the common category of the seeds by analyzing the semantic relations of the objects the words represent. To do it, we integrate information from selected Web resources. We introduce a notion of an entity network that uniformly represents the combined knowledge and allow to reason over it. We show how to use the network to disambiguate word senses by relying on a concept of optimal common ancestor and how to discover similarities between two entities. Finally, we show how to expand a set of entities, by using answer set programming with external predicates

dlvhex-sparql: A SPARQLcompliant query engine based on dlvhex

Abstract. This paper describes the dlvhex SPARQL plugin, a query processor for the upcoming Semantic Web query language standard by W3C. We report on the implementation of this languages using dlvhex, a flexible plugin system on top of the DLV solver. This work advances our earlier translation based on the semantics by Perez et al. towards an engine which is fully compliant to the official SPARQL specification. As it turns out, the differences between these two definitions of SPARQL, which might seem moderate at first glance, need some extra machinery. We also briefly report the status of implementation, and extensions currently being implemented, such as handling of aggregates, nested CONSTRUCT queries in the spirit of networked RDF graphs, or partially support of RDFS entailment. For such extensions a tight integration of SPARQL query processing and Answer-Set Programming, the underlying logic programming formalism of our engine, turns out to be particularly useful, as the resulting programs can actually involve unstratified negation.

Identification of Design Principles

This report identifies those design principles for a (possibly new) query and transformation language for the Web supporting inference that are considered essential. Based upon these design principles an initial strawman is selected. Scenarios for querying the Semantic Web illustrate the design principles and their reflection in the initial strawman, i.e., a first draft of the query language to be designed and implemented by the REWERSE working group I4

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion