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Research on multimedia information retrieval (MIR) has recently witnessed a booming interest. A prominent feature of this research trend is its simultaneous but independent materialization within several fields of computer science. The resulting richness of paradigms, methods and systems may, on the long run, result in a fragmentation of efforts and slow(More)
This paper presents a novel model of co-reference knowledge, which is based on the distinction of (i) a model of a common reality, (ii) a model of an agent's opinion about reality, and (iii) a model of agents' opinions if they talk about the same object or not. Thereby it is for the first time possible to describe consistently the evolution of the agent's(More)
According to the logical model of Information Retrieval (IR), the task of IR can be described as the extraction, from a given document base, of those documents d that, given a query q, make the formula d ! q valid, where d and q are formulae of the chosen logic and \!" denotes the brand of logical implication formalized by the logic in question. In this(More)
This paper considers Peer-to-Peer systems in which peers employ taxonomies for describing the contents of their objects and for formulating semantic-based queries to the other peers of the system. As each peer can use its own taxonomy, peers are equipped with inter-taxonomy mappings in order to carry out the required translation tasks. As these systems are(More)
  • Carlo Meghini, Fabrizio Sebastiani, Umberto Straccia, Consiglio Nazionale, Delle Ricerche
  • 1998
This chapter presents a logic for the retrieval of multimedia information, whose ultimate goal is to model retrieval as an uncertain logical inference, in accordance to the logic-based view of retrieval. The logic being presented is the product of a number of extensions to a Description Logic, which constitutes the kernel of our model. Each extension is(More)
Images are a communication medium, hence objects of a linguistic nature having a form and a content. The form of an image is the image appearance and is understood as depicting a scene, the image content. The relationship between the form of an image and its content is established through a process of interpretation, capturing the meaning of the image form.(More)
We consider the problem of query evaluation in Peer-to-Peer (P2P) systems that support semantic-based retrieval services. We confine ourselves to the case where the peers employ taxonomies for describing the contents of the objects, and articulations, i.e. inter-taxonomy map-pings, for bridging the inevitable naming, granularity and contextual(More)
We p r e s e n t a model for image retrieval in which images are represented both at the form level, as sets of physical features of the representing objects, and at the content level, as sets of logical assertions about the represented entities as well as about facts of the subject matter that are deemed as relevant for retrieval. A uniform and powerful(More)