Catálogo de publicaciones - libros

The semantic Web relies on the publication of formally represented knowledge (ontologies), retrieved and manipulated by software agents using reasoning mechanisms. OWL (Web Ontology Language), the knowledge representation language of the semantic Web, has been designed on the basis of description logics, for the use of deductive mechanisms such as classification and instantiation. Case-Based reasoning is a reasoning paradigm that relies on the reuse of cases stored in a case base. This reuse is usually performed by the adaptation of the solution of previously solved problems, retrieved from the case base, thanks to analogical reasoning. This article is about the integration of case-based reasoning into the semantic Web technologies, addressing the issue of analogical reasoning on the semantic Web. In particular, we show how OWL is extended for the representation of adaptation knowledge, and how the retrieval and adaptation steps of case-based reasoning are implemented on the basis of OWL reasoning.

In this paper, we present an approach for classifying documents based on the notion of a semantic similarity and the effective representation of the content of the documents. The content of a document is annotated and the resulting annotation is represented by a labeled tree whose nodes and edges are represented by concepts lying within a domain ontology. A reasoning process may be carried out on annotation trees, allowing the comparison of documents between each others, for classification or information retrieval purposes. An algorithm for classifying documents with respect to semantic similarity and a discussion conclude the paper.

An effective solution to the problem of extending a dialogue system to new knowledge domains requires a clear separation between the knowledge and the system: as ontologies are used to conceptualize information, they can be used as a means to improve the separation between the dialogue system and the domain information. This paper presents the development of an ontology for the cooking domain, to be integrated in a dialog system. The ontology comprehends four main modules covering the key concepts of the cooking domain – actions, food, recipes, and utensils – and three auxiliary modules – units and measures, equivalencies and plate types.

The paper describes a methodology for bootstrapping relation extraction from unstructured text in the context of GATE, but also applied to the KIM semantic annotation platform. The focus is on identifying a set of relations between entities previously found by named entity recognizer. The methodology is developed and applied to three kinds of relations and evaluated both with the ANNIE system and the default information extraction module of KIM. The methodology covers the problem of identifying the task, the target domain, the development of training and testing corpora, and useful lexical resources, the choice of a particular relation extraction approach. The application of information extraction for the Semantic Web also brings a new interesting dimension of not merely recognizing the entity type, but going into instantiation of entity references and linking them to an entity instance in a semantic repository.

We present a novel, simple, unsupervised method for characterizing the semantic relations that hold between nouns in noun-noun compounds. The main idea is to discover that make explicit the hidden relations between the nouns. This is accomplished by writing Web search engine queries that restate the noun compound as a relative clause containing a wildcard character to be filled in with a verb. A comparison to results from the literature suggest this is a promising approach.

In our research work, we explore the possibility to exploit incremental, navigational maps to build visual search-and-recommendation system. Multiple clustering algorithms may reveal distinct aspects of the document collection, just pointing to various possible meanings, and hence offer the user the opportunity to choose his/her own most appropriate perspective. We hope that such a system would become an important step on the way to information personalization. The paper presents the architectural design of our system.

In this paper, we propose a design consideration for a monitoring and diagnosing chip for the embedded system based on the model-based diagnosis. We introduce the qualitative model for the embedded system by transforming the continuous dynamics of components into the discrete state transition system, which is then further transformed into the circuit called Synchronous Boolean Network(). The faults of system components are reduced to the stuck-at faults in . We present a hardwired diagnosis engine based on Roth’s D-calculus, which allows efficient identification of the faulty parts by propagating the anomaly through the structure.

Effective automatic summarization usually requires simulating human reasoning such as abstraction or relevance reasoning. In this paper we describe a solution for this type of reasoning in the particular case of surveillance of the behavior of a dynamic system using sensor data. The paper first presents the approach describing the required type of knowledge with a possible representation. This includes knowledge about the system structure, behavior, interpretation and saliency. Then, the paper shows the inference algorithm to produce a summarization tree based on the exploitation of the physical characteristics of the system. The paper illustrates how the method is used in the context of automatic generation of summaries of behavior in an application for basin surveillance in the presence of river floods.

In order to make accessible new Semantic Web Services technologies to the end users, the level of tools supporting these technologies should be significantly raised. The paper presents the architecture of such a tool – an INFRAWBS Designer – a graphical ontology-driven tool for creating a semantic Web service description according to WSMO Framework. The tool is oriented to the end users – providers of Web services, who would like to convert their services into WSMO based semantic Web services. The most character features of the tool – intensive use of ontologies, automatic generation of logical description of a semantic service from graphical models and the use of similarity-based reasoning for finding similar service descriptions to be reused as initial templates for designing new services are discussed.