Eugenio Di Sciascio

Learn More
Motivated by the matchmaking problem in electronic marketplaces, we study abduction in Description Logics. We devise suitable definitions of the problem, and show how they can model commonsense reasoning usually employed in analyzing classified announcements having a standardized terminology. We then describe a system partially implementing these ideas, and(More)
More and more resources are becoming available on the Web, and there is a growing need for infrastructures that, based on advertised descriptions, are able to semantically match demands with supplies.We formalize general properties a matchmaker should have, then we present a matchmaking facilitator, compliant with desired properties.The system embeds a(More)
In this paper we present a Description Logic approach to extended matchmaking between Demands and Supplies in an Electronic Marketplace, which allows the semantic-based treatment of negotiable and strict requirements in the description.To this aim we exploit two novel non-standard Description Logic inference services, Concept Contraction -which extends(More)
Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of(More)
The advent of the Linked Open Data (LOD) initiative gave birth to a variety of open knowledge bases freely accessible on the Web. They provide a valuable source of information that can improve conventional recommender systems, if properly exploited. In this paper we present SPrank, a novel hybrid recommendation algorithm able to compute top-N item(More)
We present algorithms based on truth-prefixed tableaux to solve both Concept Abduction and Contraction in ALN DL. We also analyze the computational complexity of the problems, showing that the upper bound of our approach meets the complexity lower bound. The work is motivated by the need to offer a uniform approach to reasoning services useful in(More)
Reasoning engines are largely used in resource discovery and matchmaking scenarios where, given a request, they are able to provide a list of compatible items arranged in relevance order. A significant added value is the possibility to explain match outcomes in order to obtain information for modifying or refining early queries. Though the feasibility of(More)
In most real-world scenarios, the ultimate goal of recommender system applications is to suggest a short ranked list of items, namely top-<i>N</i> recommendations, that will appeal to the end user. Often, the problem of computing top-<i>N</i> recommendations is mainly tackled with a two-step approach. The system focuses first on predicting the unknown(More)
We propose a framework and polynomial algorithms for semantic-based automated Web service composition, fully compliant with Semantic Web technologies. The approach exploits the recently proposed Concept Abduction inference service in Description Logics to extend Concept covering definition to expressive logics and to solve Concept Covering problems in a(More)