In semantic matchmaking processes it is often useful, when the obtained match is not full, to provide explanations for the mismatch, to leverage further interaction and/or modifying the request. To this aim, Abduction in Description Logics has been studied, though ---till now--- on rather inexpressive languages. In this paper we present a new method for computing Abduction over complex concept descriptions in the expressive Description Logic \SH. Our proposal divides the abduced concept in pieces, which allow for direct and concise explanations. The approach exploits information within a prefixed tableau to compute solutions that take into account the structure of a formula. Hypotheses are pieces of a formula to be added inside the quantifiers of a complex concept description and not just added as outermost conjunctions. we propose suitable definitions of the problem, algorithms and calculus. we also give some hints on how to fruitfully use the proposed technique to provide rankings in the matchmaking process.
Computing Information Minimal Match Explanations for Logic-Based Matchmaking / DI NOIA, Tommaso; DI SCIASCIO, Eugenio; Donini, F. M.. - (2009), pp. 411-418. (Intervento presentato al convegno IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, WI-IAT '09 tenutosi a Milan, Italy nel 15-18 September, 2009) [10.1109/WI-IAT.2009.186].
Computing Information Minimal Match Explanations for Logic-Based Matchmaking
DI NOIA, Tommaso;DI SCIASCIO, Eugenio;
2009-01-01
Abstract
In semantic matchmaking processes it is often useful, when the obtained match is not full, to provide explanations for the mismatch, to leverage further interaction and/or modifying the request. To this aim, Abduction in Description Logics has been studied, though ---till now--- on rather inexpressive languages. In this paper we present a new method for computing Abduction over complex concept descriptions in the expressive Description Logic \SH. Our proposal divides the abduced concept in pieces, which allow for direct and concise explanations. The approach exploits information within a prefixed tableau to compute solutions that take into account the structure of a formula. Hypotheses are pieces of a formula to be added inside the quantifiers of a complex concept description and not just added as outermost conjunctions. we propose suitable definitions of the problem, algorithms and calculus. we also give some hints on how to fruitfully use the proposed technique to provide rankings in the matchmaking process.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.