Catálogo de publicaciones - libros

An hypermedia is a spatio-temporal hypertext, namely a collection of media connected by synchronization and linking relations. HyperJessSyn is a tool which uses logic programming and Semantic Web technologies for synthesizing hypermedia according to descriptions of discourse structure and of presentation layout. A rule-based system in Jess applies inference rules to interpret from an OWL graph semantic and navigation relations among media instances, and production rules to turn media contents descriptions in XML/MPEG-7 format in an XMT-A/MPEG-4 hypermedia script via XSL transformations. The system has been used to produce an hyper-guide for virtual visiting a museum.

In this paper, we describe NaviTexte, a software devoted to text navigation. First, we explain our conception of text navigation, which exploits linguistic information in texts to offer dynamic reading paths to a reader. Second, we describe a text representation specially defined to support our approach. Then we present a language for modeling navigation knowledge and its implementation framework. At last, two experimentations are presented: one aiming at teaching French at Danish students and the other one proposes text navigation as an alternative at the process of summarization based on sentences extraction.

Multimedia content annotation is a key issue in the current convergence of audiovisual entertainment and information media. In this context, automatic genre classification (AGC) provides a simple and effective solution to describe video contents in a structured and well understandable way. In this paper a method for classifying the genre of TV broadcasted programmes is presented. In our approach, we consider four groups of features, which include both low-level visual descriptors and higher level semantic information. For each type of these features we derive a characteristic vector and use it as input data of a multilayer perceptron (MLP). Then, we use a linear combination of the outputs of the four MLPs to perform genre classification of TV programmes. The experimental results on more than 100 hours of broadcasted material showed the effectiveness of our approach, achieving a classification accuracy of ~92%.

In this paper we present a hierarchical approach to text categorization aimed at improving the performances of the corresponding tasks. The proposed approach is explicitly devoted to cope with the problem related to the unbalance between relevant and non relevant inputs. The technique has been implemented and tested by resorting to a multiagent system aimed at performing information retrieval tasks.

Automatic Text Categorization (TC) is a complex and useful task for many natural language applications, and is usually performed by using a set of manually classified documents, i.e. a training collection. Term-based representation of documents has found widespread use in TC. However, one of the main shortcomings of such methods is that they largely disregard lexical semantics and, as a consequence, are not sufficiently robust with respect to variations in word usage. In this paper we design, implement, and evaluate a new text classification technique. Our main idea consists in finding a series of projections of the training data by using a new, modified LSI algorithm, projecting all training instances to the low-dimensional subspace found in the previous step, and finally inducing a binary search on the projected low-dimensional data. Our conclusion is that, with all its simplicity and efficiency, our approach is comparable to SVM accuracy on classification.

Cultural Resource Management (CRM) represents an interesting application domain for innovative approaches, models and technologies developed by computer science researchers. This paper presents NavEditOW, a system for the navigation, query and updating of ontologies through the web, as a tool providing suitable functionalities for the design and development of semantic portals in the CRM area. NavEditOW supports ontology maintainers, content editors, and end-users, that have little or no specific knowledge on Semantic Web technologies and on related formal tools. A description of the application of the tool to the representation and management of archaeological knowledge for the description of publications in an e-library is also provided.

In this work we propose some principles that regulate temporal anchorages by means of which the spectator places the events of the story on the temporal axis of the fabula, the structure where the causality and the order of the events of a story are recorded. The approach adopted for the segmentation of the story of a film uses both syntactic elements, such as the scene and the sequence, and semantic elements, such as the events of the story, defined as actions that occur in a determined interval of time (diegetic). The base representation, chosen for the analysis of the time in a story, is a particular formulation of spectator beliefs, in which the time (explicit) is present both as the element that determines the variation of spectator beliefs during the vision of the film, and also as object of belief. In this paper, we propose also a system that supplies an interactive aid (as an example to a generic expert of cinema) in order to annotate the events of the story of a film. This system supplies in addition an aid in the analysis of the flashbacks, the forwards and the repetitions of events, and may apply temporal reasoning rules to order, both partially and totally, the events of the story.

Nowadays doctors are generating a huge amount of raw data. These data, analyzed with data mining techniques, could be sources of new knowledge. Unluckily such tasks need skilled data analysts, and not so much researchers in Medicine are also data mining experts. In this paper we present a web based system for knowledge discovery assistance in Medicine able to advice a medical researcher in this kind of tasks. The user must define only the experiment specifications in a formal language we have defined. The system GUI helps users in their composition. Then the system plans a Knowledge Discovery Process (KDP) on the basis of rules in a knowledge base. Finally the system executes the KDP and produces a model as result. The system works through the co-operation of different web services specialized in different tasks. The system is still under development.

This paper deals with a knowledge representation architecture for distributed systems. The aim is to adopt a common framework to deal with an “intelligent space”, i.e., an ecosystem composed by artificial entities which cooperate to perform an intelligent multi-source data fusion. This information is used to coordinate the behavior of mobile robots and intelligent appliances. The experimental results discuss this interaction with respect to the fulfillment of complex service tasks.

This paper addresses the issue of coordinating the operations of multiple robots in an indoor environment. The framework presented here uses a composite networking architecture, in which a hybrid wireless network, composed by commonly available WiFi devices, and the more recently developed wireless sensor networks. Such architecture grants robots to enhance their perceptive capabilities and to exchange information so as to coordinate actions in order to achieve a global common goal. The proposed framework is described with reference to an experimental setup that extends a previously developed robotic tour guide application in the context of a multi-robot application.