Semantic Web Logic Programming Tools

2003 ◽  
pp. 16-32 ◽  
Author(s):  
Jóse Júlio Alferes ◽  
Carlos Viegas Damásio ◽  
Luís Moniz Pereira
Keyword(s):  
Semantic Web ◽  
Logic Programming ◽  
Programming Tools

Combining Semantic Web and Logic Programming for Agent Reasoning

2012 ◽  
pp. 428-441 ◽  
Author(s):  
Murat Şensoy ◽  
Wamberto W. Vasconcelos ◽  
Timothy J. Norman
Keyword(s):  
Semantic Web ◽  
Logic Programming

Logics for the Semantic Web

2011 ◽  
pp. 24-43
Author(s):  
J. Bruijn
Keyword(s):  
Semantic Web ◽  
Logic Programming ◽  
Description Logic ◽  
Description Logics ◽  
Order Logic ◽  
First Order Logic ◽  
Horn Logic ◽  
First Order ◽  
Logical Language ◽  
Rule Languages

This chapter introduces a number of formal logical languages which form the backbone of the Semantic Web. They are used for the representation of both ontologies and rules. The basis for all languages presented in this chapter is the classical first-order logic. Description logics is a family of languages which represent subsets of first-order logic. Expressive description logic languages form the basis for popular ontology languages on the Semantic Web. Logic programming is based on a subset of first-order logic, namely Horn logic, but uses a slightly different semantics and can be extended with non-monotonic negation. Many Semantic Web reasoners are based on logic programming principles and rule languages for the Semantic Web based on logic programming are an ongoing discussion. Frame Logic allows object-oriented style (frame-based) modeling in a logical language. RuleML is an XML-based syntax consisting of different sublanguages for the exchange of specifications in different logical languages over the Web.

scholarly journals Towards the Novel Reasoning among Particles in PSO by the Use of RDF and SPARQL

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Iztok Fister ◽  
Xin-She Yang ◽  
Karin Ljubič ◽  
Dušan Fister ◽  
Janez Brest ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Semantic Web ◽  
Query Language ◽  
The Internet ◽  
The Novel ◽  
Swarm Optimization ◽  
Significant Development ◽  
Programming Tools ◽  
New Challenges ◽  
Selection Of

The significant development of the Internet has posed some new challenges and many new programming tools have been developed to address such challenges. Today, semantic web is a modern paradigm for representing and accessing knowledge data on the Internet. This paper tries to use the semantic tools such as resource definition framework (RDF) and RDF query language (SPARQL) for the optimization purpose. These tools are combined with particle swarm optimization (PSO) and the selection of the best solutions depends on its fitness. Instead of the local best solution, a neighborhood of solutions for each particle can be defined and used for the calculation of the new position, based on the key ideas from semantic web domain. The preliminary results by optimizing ten benchmark functions showed the promising results and thus this method should be investigated further.

Introduction to the Special Issue on Logic Programming and the Web

2008 ◽  
Vol 8 (3) ◽  
pp. 247-248 ◽  
Author(s):  
MASSIMO MARCHIORI
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Logic Programming ◽  
World Wide ◽  
Special Issue ◽  
Knowledge Logic ◽  
Logical Organization ◽  
The World ◽  
The Web ◽  
Selection Of

The World Wide Web is nowadays the most famous and widespread information system. Its success is witnessed by its enormous size and rate of growth: however, the same success of the Web has brought to a situation where more sophisticated techniques are urgently needed to properly handle this mass of information. In this sense, the more ambitious plan for an evolution of a Web is the so called Semantic Web, envisioned by the inventor of the Web itself, Tim Berners-Lee. In this architectural vision, there is the need for further layers of semantics, properly enriching the data that now overflow the classic Web: ontologies, rules, logic, proofs, trust are all ingredients of this ambitious picture. Given these premises, it should not come as a surprise the fact that this evolution is bringing the Web closer and closer to another field, that since quite some time has been facing similar problems of logical organization of knowledge: logic programming. Early examples, like the Metalog system in the World Wide Web Consortium (W3C), had shown that connecting logic programming and the Semantic Web was quite a natural and fruitful step: and in fact, the burst of research in Semantic Web developments has eventually started to touch, connect and reinterprete many topics that were and are mainstream of the logic programming area. We feel this is a necessary progression, as the Semantic Web, and more generally the Web of the future, has a lot to learn from research in the logic programming area. And, conversely, in these new scenarios there are lot of new applied problems that can be challenging and rewarding from a logic programming perspective. This calls for a tighter interaction between the Web and logic programming, which was the reason to motivate this special issue as well: gathering together a selection of the best contributions that could showcase the potential of the cross-breeding.

Reconsidering Conventional Markup for Knowledge Representation

2009 ◽  
Author(s):  
David Dubin ◽  
David J. Birnbaum
Keyword(s):  
Semantic Web ◽  
Automated Reasoning ◽  
Description Logics ◽  
Manuscript Studies ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Programming Tools ◽  
Textual Transmission ◽  
Main Attraction

The main attraction of semantic web technologies such as RDF and OWL over conventional markup is the support those tools provide for expressing precise semantics. Formal grounding for RDF-based languages (in, for example, description logics) and their integration with logic programming tools are guided and constrained by issues of decidability and the tractability of computations. Users of these technologies are invited to use less expressive representations, and thereby work within those constraints. Such compromises seem reasonable when considering the roles automated reasoning agents are expected to play by the semantic web community. But where expectations differ, it may be useful to reconsider using conventional markup and inferencing methods that have been applied with success despite their theoretical weaknesses. We illustrate these issues with a case study from manuscript studies and textual transmission.

Inductive Logic Programming in Databases: From Datalog to

2010 ◽  
Vol 10 (3) ◽  
pp. 331-359 ◽  
Author(s):  
FRANCESCA A. LISI
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Logic Programming ◽  
Inductive Logic Programming ◽  
Inductive Logic ◽  
Definition Of ◽  
Deductive Power

AbstractIn this paper we address an issue that has been brought to the attention of the database community with the advent of the Semantic Web, i.e., the issue of how ontologies (and semantics conveyed by them) can help solving typical database problems, through a better understanding of Knowledge Representation (KR) aspects related to databases. In particular, we investigate this issue from the ILP perspective by considering two database problems, (i) the definition of views and (ii) the definition of constraints, for a database whose schema is represented also by means of an ontology. Both can be reformulated as ILP problems and can benefit from the expressive and deductive power of the KR framework $\mathcal{DL}+log}^{\neg\vee}$. We illustrate the application scenarios by means of examples.

scholarly journals XSB: Extending Prolog with Tabled Logic Programming

2011 ◽  
Vol 12 (1-2) ◽  
pp. 157-187 ◽  
Author(s):  
TERRANCE SWIFT ◽  
DAVID S. WARREN
Keyword(s):  
Semantic Web ◽  
Logic Programming ◽  
Large Class ◽  
Program Analysis

AbstractThe paradigm of Tabled Logic Programming (TLP) is now supported by a number of Prolog systems, including XSB, YAP Prolog, B-Prolog, Mercury, ALS, and Ciao. The reasons for this are partly theoretical: tabling ensures termination and optimal known complexity for queries to a large class of programs. However, the overriding reasons are practical. TLP allows sophisticated programs to be written concisely and efficiently, especially when mechanisms such as tabled negation and call and answer subsumption are supported. As a result, TLP has now been used in a variety of applications from program analysis to querying over the semantic web. This paper provides a survey of TLP and its applications as implemented in the XSB Prolog, along with discussion of how XSB supports tabling with dynamically changing code, and in a multi-threaded environment.

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

2008 ◽  
Vol 8 (3) ◽  
pp. 271-300 ◽  
Author(s):  
FRANCESCA A. LISI
Keyword(s):  
Semantic Web ◽  
Logic Programming ◽  
Inductive Logic Programming ◽  
Description Logic ◽  
Ad Hoc ◽  
Inductive Logic ◽  
Knowledge Representation And Reasoning ◽  
Reasoning Systems ◽  
Hybrid Knowledge ◽  
Deductive Power

AbstractBuilding rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim, an ad-hoc markup 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 languageDatalog. 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 versus 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.

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