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..., we may ask “find a car costing around $15000” (see [12]); or in ontology-mediated access to multimedia information, we may ask “find images about cars, which are similar to a given one” (see, e.g., =-=[11,19]-=-). Unlike the classical case, tuples now satisfy these queries to a degree (usually in [0, 1]). Therefore, a major problem is that now an answer is a set of tuples ranked according to their degree. Th...

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...s, including music stored in various representational formats. The primary focus is on usability issues relating to the modalities employed in the interaction between user and system. As others (e.g. =-=[14]-=-) have noted, there is a ‘medium mismatch problem’ when documents and queries are expressed in different media; our work investigates this problem from a usability perspective, considering both the us...

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...et, we can also apply a different ranking functions by either relying on non-crisp entailments, e.g. by making use of a logical language that allow for ranking using a relevance terminological logic (=-=Meghini et al., 2001-=-) or by relying on ranking mechanisms such as defined by Ding et al. (2005) or by Siberski et al. (2006). 5 AN EXPRESSIVE SYSTEM RESOURCE MODEL In this section, we describe in detail the adopted syste...

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...its architecture, its representation and query language and the preliminary experiments we conducted. Overall, DL-MEDIA lies in the context of Logic-based Multimedia Information Retrieval (LMIR) (see =-=[11]-=- for an extensive overview on LMIR literature. A recent work is also e.g. [9], see also [10] and [4] for a more complex multimedia ontology model). 2 The DL-MEDIA architecture In DL-MEDIA, from each m...

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...ly off-line) by a specific system. For instance, we may have an underlying image retrieval system that for each identified object in an image has m scores, one for each of the m attributes (see, e.g. =-=[8]-=-). The intentional database is a set of rules in which all variables in the head do also appear in the rule body. To facilitate the reading, we first give an example of rule with its intended meaning ...

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...role names. 3 Horn rules in fuzzy CARIN: The Horn rule component H of a fuzzy CARIN knowledge base K contains a set of Horn rules that are logical sentences of the form: p1(X1) ∧ ... ∧ pk(Xk) ⇒ q(Y ) =-=(2)-=- where X1, · · · ,Xk and Y are tuples of variables and individuals and p1, · · · pk may be concept names, roles or ordinary predicates while q is always an ordinary predicate. The antecedents of a Hor...

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... (x) ⇒ D I (x)} Semantics of fuzzy concepts and axioms. K as bsd(K, C) = sup I|=K sup x∈∆ I C I (x). Example 1: Assume we would like to recognize whether there is a quite house in an image (see, e.g. =-=[13]-=-), where a quite house is defined as a house having a garden around. Assume that we have a definition for quite house and the output of a (semi-automatic) image classification tool applied to an image...

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...and endowing with content each so created view (e.g. the section in Figure 1). For simplicity, our model will only consider contents of type text, even though the extension to other types is possible =-=[14]-=-. As far as structure is concerned, we consider ordered sets and sequences. The former kind is useful to model views whose elements are, albeit ordered for formal reasons, to be regarded as likewise; ...