Information sharing from multiple heterogeneous sources is a challenging issue which ranges from database to ontology areas. In this paper, we propose an intelligent approach to information integration which takes into account semantic conflicts and contradictions, caused by the lack of a common shared ontology. Our goal is to provide an integrated access to information sources, allowing a user to pose a single query and to receive a single unified answer. We propose a ldquosemanticrdquo approach for integration where the conceptual schema of each source is provided, adopting a common standard data model and language. Description logics plus clustering techniques are exploited. Description logics are used to obtain a semi-automatic generation of a common thesaurus (to solve semantic heterogeneities and to derive a common ontology) while clustering techniques are employed to build the global schema, i.e. the unified view of the data to be used for query processing
An intelligent approach to information integration / S. Bergamaschi, S. Castano, S. De Capitani di Vimercati, S. Montanari, M. Vincini - In: Formal Ontology in Information Systems[s.l] : IOS Press, 1998. (( convegno Proceedings of Formal Ontology in Information Systems tenutosi a Trento, Italy nel 6-8 June 1998.
An intelligent approach to information integration
S. CastanoSecondo
;S. De Capitani di Vimercati;
1998
Abstract
Information sharing from multiple heterogeneous sources is a challenging issue which ranges from database to ontology areas. In this paper, we propose an intelligent approach to information integration which takes into account semantic conflicts and contradictions, caused by the lack of a common shared ontology. Our goal is to provide an integrated access to information sources, allowing a user to pose a single query and to receive a single unified answer. We propose a ldquosemanticrdquo approach for integration where the conceptual schema of each source is provided, adopting a common standard data model and language. Description logics plus clustering techniques are exploited. Description logics are used to obtain a semi-automatic generation of a common thesaurus (to solve semantic heterogeneities and to derive a common ontology) while clustering techniques are employed to build the global schema, i.e. the unified view of the data to be used for query processingPubblicazioni consigliate
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