Search results for "Ontology alignment"

showing 10 items of 12 documents

A Context-Based Enterprise Ontology

2007

The main purpose of an enterprise ontology is to promote the common understanding between people across enterprises, as well as to serve as a communication medium between people and applications, and between different applications. This paper outlines a top-level ontology, called the context-based enterprise ontology, which aims to advance the understanding of the nature, purposes and meanings of things in enterprises with providing basic concepts for conceiving, structuring and representing things within contexts and/or as contexts. The ontology is based on the contextual approach according to which a context involves seven domains: purpose, actor, action, object, facility, location, and t…

Knowledge managementbusiness.industryComputer scienceOntology-based data integrationProcess ontologySuggested Upper Merged OntologyOntology (information science)computer.software_genreOntology engineeringWorld Wide WebOntology chartUpper ontologybusinessOntology alignmentcomputer
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Locality-Sensitive Hashing for Massive String-Based Ontology Matching

2014

This paper reports initial research results related to the use of locality-sensitive hashing (LSH) for string-based matching of big ontologies. Two ways of transforming the matching problem into a LSH problem are proposed and experimental results are reported. The performed experiments show that using LSH for ontology matching could lead to a very fast matching process. The quality of the alignment achieved in these experiments is comparable to state-of-the-art matchers, but much faster. Further research is needed to find out whether the use of different metrics or specific hardware would improve the results. peerReviewed

Matching (statistics)Computer sciencebusiness.industryString (computer science)Hash functionBig datastring-based ontology matchingProcess (computing)computer.software_genreLocality-sensitive hashinglocality-sensitive hashingData miningbusinessOntology alignmentcomputer2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)
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A literature review of sensor ontologies for manufacturing applications

2013

The purpose of this paper is to review existing sensor and sensor network ontologies to understand whether they can be reused as a basis for a manufacturing perception sensor ontology, or if the existing ontologies hold lessons for the development of a new ontology. We develop an initial set of requirements that should apply to a manufacturing perception sensor ontology. These initial requirements are used in reviewing selected existing sensor ontologies. Additionally, we present our developed sensor ontology thus far that incorporates a refined list of requirements. This paper describes 1) extending and refining the requirements; 2) proposing hierarchical structures for verifying the purpo…

Ontology Inference LayerDatabaseComputer sciencebusiness.industrycomputer.internet_protocolOntology-based data integrationProcess ontologySuggested Upper Merged OntologyOntology (information science)computer.software_genreOWL-SUpper ontologySoftware engineeringbusinesscomputerOntology alignment2013 IEEE International Symposium on Robotic and Sensors Environments (ROSE)
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A Survey on Ontology Evaluation Methods

2015

International audience; Ontologies nowadays have become widely used for knowledge representation, and are considered as foundation for Semantic Web. However with their wide spread usage, a question of their evaluation increased even more. This paper addresses the issue of finding an efficient ontology evaluation method by presenting the existing ontology evaluation techniques, while discussing their advantages and drawbacks. The presented ontology evaluation techniques can be grouped into four categories: gold standard-based, corpus-based, task-based and criteria based approaches.

Ontology Inference Layer[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-TT ] Computer Science [cs]/Document and Text ProcessingComputer sciencecomputer.internet_protocolProcess ontology[ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyOntology (information science)OWL-S[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]020204 information systems0202 electrical engineering electronic engineering information engineeringUpper ontology[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]EvaluationInformation retrievalOntologyOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebSuggested Upper Merged Ontology[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-TT]Computer Science [cs]/Document and Text Processing[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]020201 artificial intelligence & image processing[ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO]computerOntology alignmentSemantic web
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Ontology Views for Ontology Change Management

2014

International audience; In the literature, ontology change management systems (OCMS) are direct implementation of the concept of “change management” stated by reference (Klein, 2004). Ontology change management combines ontol- ogy evolution and versioning features to manage ontol- ogy changes and their impacts. Since 2007, many works have combined ontology evolution and versioning into ontology change management systems (OCMS). The evolution subject has been massively studied in these works. They especially addressed the consistence issue for the application of changes on the ontology. These proposals constituted a consequent background for ontology change management but they did not take i…

Ontology Inference Layer[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationComputer scienceProcess ontologyURI[ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyOntology (information science)computer.software_genreRDFOpen Biomedical Ontologies[INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]ontology evolution0202 electrical engineering electronic engineering information engineeringUpper ontologyontologyOWL DLOWLInformation retrievalOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebSuggested Upper Merged Ontologymaterialized view020207 software engineering[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation[ INFO.INFO-FL ] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]database viewontology mapping020201 artificial intelligence & image processingData miningComputingMethodologies_GENERALontology change managementOntology alignmentcomputer
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Model Driven Specification of Ontology Translations

2008

The alignment of different ontologies requires the specification, representation and execution of translation rules. The rules need to integrate translations at the lexical, the syntactic and the semantic layer requiring semantic reasoning as well as low-level specification of ad-hoc conversions of data. Existing formalisms for representing translation rules cannot cover the representation needs of these three layers in one model. We propose a metamodel-based representation of ontology alignments that integrate semantic translations using description logics and lower level translation specifications into one model of representation for ontology alignments.

Ontology Inference Layerbusiness.industryProgramming languageComputer scienceOntology-based data integrationProcess ontologySuggested Upper Merged Ontology02 engineering and technologyOntology (information science)computer.software_genreDescription logic020204 information systems0202 electrical engineering electronic engineering information engineeringUpper ontology020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerOntology alignmentNatural language processingLecture Notes in Computer Science Conceptual Modeling - ER 2008
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Ontology-based service matching and discovery

2011

In this paper we consider ontologies as knowledge structures that specify attributes of services, their properties and relations among them to enable finding semantic similarity between service descriptions and service requests. Ontologies reflect semantic relationship between concepts represented by attributes in service descriptions and service requests. We use knowledge from ontologies to enhance the both user service requests and service descriptions by adding concepts that are not presented in the original descriptions, and use them in comparison process. It results in more precise matching since we consider also implicit concepts. Thus services and requests that do not contain exact m…

Service (business)World Wide WebMatching (statistics)Information retrievalSemantic similarityComputer scienceService discoveryOntology (information science)Web serviceSemanticscomputer.software_genreOntology alignmentcomputerProceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems
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Learning Path Generation by Domain Ontology Transformation

2005

An approach to automated learning path generation inside a domain ontology supporting a web tutoring system is presented. Even if a terminological ontology definition is needed in real systems to enable reasoning and/or planning techniques, and to take into account the modern learning theories, the task to apply a planner to such an ontology is very hard because the definition of actions along with their preconditions and effects has to take into account the semantics of the relations among concepts, and it results in building an ontology of learning. The proposed methodology is inspired to the Knowledge Space Theory, and proposes some heuristics to transform the original ontology in a weig…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniOntology Inference LayerTheoretical computer scienceKnowledge spaceComputer sciencecomputer.internet_protocolbusiness.industryOntology-based data integrationProcess ontologySuggested Upper Merged OntologyOntology (information science)computer.software_genreSemanticsExpert systemOWL-STerminologyData modelOntologyUpper ontologyArtificial intelligenceautomated learning pathbusinesscomputerOntology alignment
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Ontology languages for the semantic web: A never completely updated review

2006

This paper gives a never completely account of approaches that have been used for the research community for representing knowledge. After underlining the importance of a layered approach and the use of standards, it starts with early efforts used for artificial intelligence researchers. Then recent approaches, aimed mainly at the semantic web, are described. Coding examples from the literature are presented in both sections. Finally, the semantic web ontology creation process, as we envision it, is introduced.

Web standardsOntology Inference LayerInformation Systems and ManagementKnowledge representation and reasoningComputer sciencecomputer.internet_protocolProcess ontologyOntology (information science)computer.software_genreSocial Semantic WebOWL-SManagement Information SystemsWorld Wide WebOpen Biomedical OntologiesArtificial IntelligenceSemantic computingSemantic analyticsUpper ontologySemantic Web StackSemantic Webbusiness.industryOntology-based data integrationSuggested Upper Merged OntologyOntology languageOntologyArtificial intelligencebusinessWeb intelligencecomputerOntology alignmentSoftwareNatural language processingKnowledge-Based Systems
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Representing and Reasoning for Spatiotemporal Ontology Integration

2004

International audience; The World-Wide Web hosts many autonomous and heterogeneous information sources. In the near future each source may be described by its own ontology. The distributed nature of ontology development will lead to a large number of local ontologies covering overlapping domains. Ontology integration will then become an essential capability for effective interoperability and information sharing. Integration is known to be a hard problem, whose complexity increases particularly in the presence of spatiotemporal information. Space and time entail additional problems such as the heterogeneity of granularity used in representing spatial and temporal features. Spatio-temporal ob…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Information retrieval[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO]Computer scienceOntologyProcess ontologyOntology-based data integrationSuggested Upper Merged OntologyIntegration[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]Spatio-Temporal data02 engineering and technologyOntology (information science)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Open Biomedical OntologiesMapping020204 information systemsOntology components0202 electrical engineering electronic engineering information engineeringUpper ontology020201 artificial intelligence & image processingOntology alignment
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