Catálogo de publicaciones - libros

We view as an operator that takes two graph-like structures (e.g., classifications, XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. is based on two ideas: (i) we discover mappings by computing (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the (concepts, not labels) which is codified in the elements and the structures of schemas. In this paper we present basic and optimized algorithms for semantic matching, and we discuss their implementation within the S-Match system. We evaluate S-Match against three state of the art matching systems, thereby justifying empirically the strength of our approach.

In this paper we illustrate an approach for clustering semantically heterogeneous XML Schemas. The proposed approach is driven by the semantics of the involved Schemas that is defined by means of the interschema properties existing among concepts represented therein; interschema properties taken into account by our approach are synonymies (indicating that two concepts have the same meaning), hyponymies (denoting that a concept has a more specific meaning than another one), and overlappings (indicating that two concepts are neither synonyms nor one hyponym of the other, but represent, to some extent, the same reality). An important feature of our approach consists of its capability of being integrated with almost all the clustering algorithms already proposed in the literature. Both a theoretical and an experimental analysis on the complexity of our approach are presented in the paper. They show that our approach is scalable and particularly suited in application contexts characterized by a great number and a large variety of XML Schemas.

For several reasons enterprises are frequently subject to organizational change. Respective adaptations may concern business processes, but also other components of an enterprise architecture. In particular, changes of organizational structures often become necessary. The information about organizational entities and their relationships is maintained in organizational models. Therefore the quick and correct adaptation of these models is fundamental to adequately cope with organizational changes. However, model changes alone are not sufficient to guarantee consistency. Since organizational models also provide the basis for defining access rules (e.g., actor assignments in workflow management systems or access rules in document-centered applications) this information has to be adapted accordingly (e.g., to avoid dangling references or non-resolvable actor assignments). Current approaches do not adequately address this problem, which often leads to security gaps and delayed change implementation.In this paper we introduce a formal framework for the controlled evolution of organizational models and related access rules. Firstly, we introduce a set of operators with well-defined semantics for defining and changing organizational models. Secondly, we show how to define access rules based on such models. In this context we also define a notion of correctness for access rules. Thirdly, we present a formal framework for the (semi-automated) adaptation of access rules when the underlying organizational model is changed by exploiting the semantics of the applied changes. Altogether the presented approach provides an important contribution for realizing adaptive access control frameworks.

Ontologies and contexts are complementary disciplines for modeling views. In the area of information integration, ontologies may be viewed as the outcome of a manual effort to model a domain, while contexts are system generated models. In this work, we provide a formal mathematical framework that delineates the relationship between contexts and ontologies. We then use the model to handle the uncertainty associated with automatic context extraction from existing documents by providing a ranking method, which ranks ontology concepts according to their suitability to a given context. Throughout this work we motivate our research using QUALEG, a European IST project that aims providing local governments with an effective tool for bi-directional communication with citizens. We empirically evaluate our model using two real-world data sets, coming from Reuters and news RSS. Our empirical analysis shows that the input needed to accurately define a concept by a context is small, and the classification of documents to concepts is accurate.

Due to the inherent difficulties associated with manual ontology building, knowledge acquisition approaches such as ontology reuse or ontology learning from texts are often seen as instruments that can make this tedious process easier. In this paper we present a NLP-based method to aid ontology design in a specific application scenario, namely that in which the resulting ontology is used to support the semantic annotation of text documents. The proposed method uses the World Wide Web in its analysis of the domain-specific documents, thereby greatly reducing the need for linguistic expertise and resources, and suggests ways to specify domain ontologies in a “linguistics-friendly” format in order to improve further ontology-based natural language processing tasks such as semantic annotation. We present a thorough evaluation of the method, using corpora from three diverse real-world settings (medical information, tourism, and recipes). Additionally, for the first scenario we compare the costs and the benefits of the NLP-based ontology engineering approach against a similar, reuse-oriented experiment.

Annotation with security-related metadata enables discovery of resources that meet security requirements. This paper presents the NRL Security Ontology, which complements existing ontologies in other domains that focus on annotation of functional aspects of resources. Types of security information that could be described include mechanisms, protocols, objectives, algorithms, and credentials in various levels of detail and specificity. The NRL Security Ontology is more comprehensive and better organized than existing security ontologies. It is capable of representing more types of security statements and can be applied to any electronic resource. The class hierarchy of the ontology makes it both easy to use and intuitive to extend. We applied this ontology to a Service Oriented Architecture to annotate security aspects of Web service descriptions and queries. A refined matching algorithm was developed to perform requirement-capability matchmaking that takes into account not only the ontology concepts, but also the properties of the concepts.