Catálogo de publicaciones - libros

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. The idea is to improve, on the one hand, the results of Web Mining by exploiting the new semantic structures in the Web; and to make use of Web Mining, on the other hand, for building up the Semantic Web. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.

There are two major ongoing efforts to advance the World Wide Web. On one side there is the Semantic Web research, on the other side is the Web Service research. Both activities aim to make content on the web accessible and usable not only for humans but also for machines in order to create a foundation for intelligent automated services and business processes. These two efforts are highly complementary, and there is work in progress towards a unification of them. This paper contributes to this process of unification by presenting a method of connecting Web Services descriptions with Semantic Web ontologies.

The idea of knowledge sharing has strong roots in the education process. With the current development of the technology and moving learning material into the web environment it acquired a new dimension. Learning objects are the chunks of knowledge shared by e-learning community. Organizations and individuals are building repositories of learning objects and annotate them with metadata to describe their educational values and standardization efforts are on the way to provide a franca lingua for the educators. In this paper we describe the peer-to-peer infrastructure for sharing learning object we are building in Canada. The POOL projects builds on the three types of nodes: SPLASH is an freely downloadable application which allows individuals to create metadata and maintain their collection of learning objects, PONDs are bigger repositories of learning objects connected to the peer-to-peer network and POOL centrals increase the speed and breadth of the searches in the peer-to-peer network. The POOL project uses CanCore - a subset of the IMS metadata protocol - to describe learning objects. In the second part of the paper we discuss the future direction of this initiative based on the maturing learning objects community and lessons learned in the deployment of POOL network. We argue that the standardization effort, although very important, currently provides solutions that are too complex. We see the communities where the knowledge is shared to be the main force in the creation of the metadata standards which would support the growth of semantic web. The implications of moving the responsibility for schemas and metadata creation on communities poses new requirements on interoperability and tools. We describe those requirements and we outline approach we are developing to address them.

Entailment, as defined by RDF’s model-theoretical semantics, is a basic requirement for processing RDF, and represents the kind of “semantic interoperability” that RDF-based systems have been anticipated to have to realize the vision of the “Semantic Web”. In this paper we give some results in our investigation of a practical implementation of the entailment rules, based on the graph-walking query mechanism of the Wi lbur RDF toolkit.

The DARPA Agent Markup Language ontology for Services (DAML-S) enables the description of Web-based services, such that they can be discovered, accessed and composed dynamically by intelligent software agents and other Web services, thereby facilitating the coordination between distributed, heterogeneous systems on the Web. We propose a formalised syntax and an initial reference semantics for DAML-S, which incorporates subtype polymorphism. The semantics we describe is derived from the semantics for Erlang and Concurrent Haskell. We contrast our semantics with an alternate semantics proposed for DAML-S, based on the situation calculus and Petri nets.

The Web is moving from being a collection of pages toward a collection of services that interoperate through the Internet. The first step toward this interoperation is the location of other services that can help toward the solution of a problem. In this paper we claim that location of web services should be based on the semantic match between a declarative description of the service being sought, and a description of the service being offered. Furthermore, we claim that this match is outside the representation capabilities of registries such as UDDI and languages such as WSDL. We propose a solution based on DAML-S, a DAML-based language for service description, and we show how service capabilities are presented in the Profile section of a DAML-S description and how a semantic match between advertisements and requests is performed.

In this paper we present DAML-S, a DAML+OIL ontology for describing the properties and capabilities of Web Services. Web Services - Web-accessible programs and devices - are garnering a great deal of interest from industry, and standards are emerging for low-level descriptions of Web Services. DAML-S complements this effort by providing Web Service descriptions at the application layer, describing what a service can do, and not just how it does it. In this paper we describe three aspects of our ontology: the service profile, the process model, and the service grounding. The paper focuses on the grounding, which connects our ontology with low-level XML-based descriptions of Web Services.

This paper presents TRIPLE, a layered and modular rule language for the Semantic Web [ 1 ]. TRIPLE is based on Horn logic and borrows many basic features from F-Logic [ 11 ] but is especially designed for querying and transforming RDF models [ 20 ]. TRIPLE can be viewed as a successor of SiLRI (Simple Logic-based RDF Interpreter [ 5 ]). One of the most important differences to F-Logic and SiLRI is that TRIPLE does not have a fixed semantics for object-oriented features like classes and inheritance. Its layered architecture allows such features to be easily defined for different object-oriented and other data models like UML, Topic Maps, or RDF Schema [ 19 ]. Description logics extensions of RDF (Schema) like OIL [ 17 ] and DAML+OIL [ 3 ] that cannot be fully handled by Horn logic are provided as modules that interact with a description logic classifier, e.g. FaCT [ 9 ], resulting in a hybrid rule language. This paper sketches syntax and semantics of TRIPLE.

A marketplace is the place in which the demand and supply of buyers and vendors participating in a business process may meet. Therefore, electronic marketplaces are virtual communities in which buyers may meet proposals of several suppliers and make the best choice. In the electronic commerce world, the comparison between different products is blocked due to the lack of standards (on the contrary, the proliferation of standards) describing and classifying them. Therefore, the need for B2B and B2C marketplaces is to reclassify products and goods according to different standardization models. This paper aims to face this problem by suggesting the use of a semi-automatic methodology, supported by a tool (SI-Designer), to define the mapping among different e-commerce product classification standards. This methodology was developed for the MOMIS system within the Intelligent Integration of Information research area. We describe our extension to the methodology that makes it applyable in general to product classification standard, by selecting a fragment of ECCMA/UNSPSC and ecl@ss standard.

The development of the Semantic Web proceeds in layers. Currently the most advanced layer that has reached maturity is the ontology layer, in the from of the DAML+OIL language which corresponds to a rich description logic. The next step will be the the realization of logical rule systems on top of the ontology layer. Computationally simple nonmonotonic rule systems show promise to play an important role in electronic commerce on the Semantic Web. In this paper we outline how nonmonotonic rule systems in the form of defeasible reasoning, can be built on top of description logics.