VEBO: Validation of E-R diagrams through ontologies and WordNet

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4 Citazioni (Scopus)

Abstract

In the semantic web vision, ontologies are building blocks for providing applications with a high level description of the operating environment in support of interoperability and semantic capabilities. The importance of ontologies in this respect is clearly stated in many works. Another crucial issue to increase the semantic aspect of web is to enrich the level of expressivity of database related data. Nowadays, databases are the primary source of information for dynamical web sites. The linguistic data used to build the database structure could be relevant for extracting meaningful information. In most cases, this type of information is not used for information retrieval. The work presented in this paper deals with an attempt to enrich a database structure using linguistic information. The purpose is twofold: the proposed approach can be used either to validate the database structure linguistically or at least to enrich information retrieval with structural information. In this paper the first goal is pursued by the construction of the VEBO system that is used to validate database entity-relation diagrams through semi-automatic creation and enrichment of ontology.
Lingua originaleEnglish
Stato di pubblicazionePublished - 2012

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Ontology
Information retrieval
Linguistics
Semantics
Semantic Web
Interoperability
Websites

All Science Journal Classification (ASJC) codes

  • Software

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abstract = "In the semantic web vision, ontologies are building blocks for providing applications with a high level description of the operating environment in support of interoperability and semantic capabilities. The importance of ontologies in this respect is clearly stated in many works. Another crucial issue to increase the semantic aspect of web is to enrich the level of expressivity of database related data. Nowadays, databases are the primary source of information for dynamical web sites. The linguistic data used to build the database structure could be relevant for extracting meaningful information. In most cases, this type of information is not used for information retrieval. The work presented in this paper deals with an attempt to enrich a database structure using linguistic information. The purpose is twofold: the proposed approach can be used either to validate the database structure linguistically or at least to enrich information retrieval with structural information. In this paper the first goal is pursued by the construction of the VEBO system that is used to validate database entity-relation diagrams through semi-automatic creation and enrichment of ontology.",
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AU - Pirrone, Roberto

AU - Gentile, Antonio

AU - Russo, Giuseppe

AU - Pipitone, Arianna

AU - Anastasio, Francesca

PY - 2012

Y1 - 2012

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AB - In the semantic web vision, ontologies are building blocks for providing applications with a high level description of the operating environment in support of interoperability and semantic capabilities. The importance of ontologies in this respect is clearly stated in many works. Another crucial issue to increase the semantic aspect of web is to enrich the level of expressivity of database related data. Nowadays, databases are the primary source of information for dynamical web sites. The linguistic data used to build the database structure could be relevant for extracting meaningful information. In most cases, this type of information is not used for information retrieval. The work presented in this paper deals with an attempt to enrich a database structure using linguistic information. The purpose is twofold: the proposed approach can be used either to validate the database structure linguistically or at least to enrich information retrieval with structural information. In this paper the first goal is pursued by the construction of the VEBO system that is used to validate database entity-relation diagrams through semi-automatic creation and enrichment of ontology.

KW - Ontology; e-r Diagrams;

UR - http://hdl.handle.net/10447/75599

M3 - Paper

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