Search results for " Knowledge representation languages"

showing 2 items of 2 documents

An Innovative Statistical Tool for Automatic OWL-ERD Alignment

2016

Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corre…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalRelation (database)computer.internet_protocolComputer scienceSemantic Web Rule LanguageComputer Science::Information Retrieval010401 analytical chemistry020206 networking & telecommunications02 engineering and technologyOntology (information science)SemanticsSemantic data model01 natural sciencesOWL-S0104 chemical sciences0202 electrical engineering electronic engineering information engineeringHidden Markov models Knowledge representation languages Ontologies (artificial intelligence) Semantic Web Databases OWL ERDSemantic WebcomputerSentence2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
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HOWERD: A Hidden Markov Model for Automatic OWL-ERD Alignment

2016

The HOWERD model for estimating the most likely alignment between an OWL ontology and an Entity Relation Diagram (ERD) is presented. Automatic alignment between relational schema and ontology represents a big challenge in Semantic Web research due to the different expressiveness of these representations. A relational schema is less expressive than the ontology; this is a non trivial problem when accessing data via an ontology and for ontology storing by means of a relational schema. Existent alignment methodologies fail in loosing some contents of the involved representations because the ontology captures more semantic information, and several elements are left unaligned. HOWERD relies on a…

computer.internet_protocolComputer scienceProcess ontology02 engineering and technologyOntology (information science)computer.software_genre01 natural sciencesOWL-S0202 electrical engineering electronic engineering information engineeringUpper ontologyHidden Markov modelcomputer.programming_languageSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer Science::Information RetrievalOntology-based data integration010401 analytical chemistry020207 software engineeringWeb Ontology Language0104 chemical sciencesHidden Markov models Knowledge representation languages Ontologies (artificial intelligence) Semantic Web Databases OWL ERDArtificial intelligencebusinesscomputerOntology alignmentNatural language processing2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
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