Umberto Straccia

Reasoning within fuzzy description logics

Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e. set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadehs fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.

Managing uncertainty and vagueness in description logics for the Semantic Web

Ontologies play a crucial role in the development of the Semantic Web as a means for defining shared terms in web resources. They are formulated in web ontology languages, which are based on expressive description logics. Significant research efforts in the semantic web community are recently directed towards representing and reasoning with uncertainty and vagueness in ontologies for the Semantic Web. In this paper, we give an overview of approaches in this context to managing probabilistic uncertainty, possibilistic uncertainty, and vagueness in expressive description logics for the Semantic Web.

fuzzyDL: An expressive fuzzy description logic reasoner

In this paper we present fuzzyDL, an expressive fuzzy description logic reasoner.We present its salient features, including some novel concept constructs and queries, and examples of use cases: matchmaking and fuzzy control.

Fuzzy ontology representation using OWL 2

The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing a procedure to represent such information within current standard languages and tools. In this work, we follow the latter approach, by identifying the syntactic differences that a fuzzy ontology language has to cope with, and by proposing a concrete methodology to represent fuzzy ontologies using OWL 2 annotation properties. We also report on some prototypical implementations: a plug-in to edit fuzzy ontologies using OWL 2 annotations and some parsers that translate fuzzy ontologies represented using our methodology into the languages supported by some reasoners.

Web metasearch: rank vs. score based rank aggregation methods

Given a set of rankings, the task of ranking fusion is the problem of combining these lists in such a way to optimize the performance of the combination. The ranking fusion problem is encountered in many situations and, e.g., metasearch is a prominent one. It deals with the problem of combining the result lists returned by multiple search engines in response to a given query, where each item in a result list is ordered with respect to a search engine and a relevance score. Several ranking fusion methods have been proposed in the literature. They can be classified based on whether: (i) they rely on the rank; (ii) they rely on the score; and (iii) they require training data or not. Our paper will make the following contributions: (i) we will report experimental results for the Markov chain rank based methods, for which no large experimental tests have yet been made; (ii) while it is believed that the rank based method, named Borda Count, is competitive with score based methods, we will show that this is not true for metasearch; and (iii) we will show that Markov chain based methods compete with score based methods. This is especially important in the context of metasearch as scores are usually not available from the search engines.

Towards a fuzzy description logic for the semantic web (preliminary report)

In this paper we present a fuzzy version of

A model of multimedia information retrieval

\mathcal{SHOIN}

A general framework for representing, reasoning and querying with annotated Semantic Web data

(D), the corresponding Description Logic of the ontology description language OWL DL. We show that the representation and reasoning capabilities of fuzzy

Transforming Fuzzy Description Logics into Classical Description Logics

\mathcal{SHOIN}

Fuzzy description logics with general t-norms and datatypes

(D) go clearly beyond classical