OMEN: A Probabilistic Ontology Mapping Tool

Mitra, Prasenjit; Noy, Natalya F.; Jaiswal, Anuj R.

doi:10.1007/11574620_39

Cited by 98 publications

(60 citation statements)

References 3 publications

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“…In general, the concepts of two different ontologies do not match exactly, and we have to deal with degrees of concept overlap as above, which are determined by automatic or semi-automatic tools or experts. These degrees of concept overlap are then represented in probabilistic ontologies, which thus allows for inference about the degrees of overlap between other concepts and about probabilistic instance relationships [104,98] (see also Section 4.5.2).…”

Section: Main Applicationsmentioning

confidence: 99%

“…In closely related work, Mitra et al [98] describe an implemented technique, called Omen, to enhancing existing ontology mappings by using a Bayesian network to represent the influences between potential concept mappings across ontologies. More concretely, Omen is based on a simple ontology model similar to RDF Schema.…”

Section: Probabilistic Web Ontology Languagesmentioning

confidence: 99%

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Managing uncertainty and vagueness in description logics for the Semantic Web

Lukasiewicz

Straccia

2008

Journal of Web Semantics

328

101

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a b s t r a c tOntologies play a crucial role in the development of the Semantic Web as a means for defining shared terms in web resources. They are formulated in web ontology languages, which are based on expressive description logics. Significant research efforts in the semantic web community are recently directed towards representing and reasoning with uncertainty and vagueness in ontologies for the Semantic Web. In this paper, we give an overview of approaches in this context to managing probabilistic uncertainty, possibilistic uncertainty, and vagueness in expressive description logics for the Semantic Web.

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Section: Main Applicationsmentioning

confidence: 99%

Section: Probabilistic Web Ontology Languagesmentioning

confidence: 99%

Managing uncertainty and vagueness in description logics for the Semantic Web

Lukasiewicz

Straccia

2008

Journal of Web Semantics

328

101

View full text Add to dashboard Cite

show abstract

“…• Complement experiments at universities in order to validate the results of the interviews and modelling sessions against the visionary challenge of the IT-Socket • Extensive survey in the literature [3], [7], [10], [14], [23], [29], [31], [40] and [48] The result of the analysis, as shown in Fig 1, was the definition of three aspects for both the business and IT perspective: the competence aspects -providing the human knowledge, technical aspects -consisting of software, hardware and IT infrastructure and organisational aspects -taking over responsibility for parts of the IT-Infrastructure. They are divided on the perspective basis and include:…”

Section: The Analysis Of the It-socketmentioning

confidence: 99%

The IT-Socket: Model-Based Realisation of the Business and IT Alignment Framework

Woitsch¹,

Utz²,

Hrgovcic³

2009

Lecture Notes in Business Information Processing

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Abstract. As a result of recent changes in the IT, where the role of IT has shifted from an enabler to an industrial sector in its own right, the necessity to provide framework which would allow seamless alignment of the business and IT rose. The goal was to allow the stakeholders from the business as well as IT perspective to model the requirements for the IT service provisioning using the modeling languages they are familiar with and to apply semantic technologies as a mediator that will allow translation between them. IT-Socket, the model based approach for business and IT alignment, developed in the European Research project -plugIT, aims to realize the vision of businesses "plugging-in" to IT by introducing graphical modeling languages as mediators between the domain experts and IT. The research challenges identified include the ability to perform integration and translation between graphical modeling languages by building the reference ontology, enabling automatic generation of machine interpretable domain ontologies from graphical models and allowing automatic translation between domain ontologies. The results of the application of the ITSocket for business and IT alignment are presented within three use cases: (1) "Certification" of IT infrastructure, (2) "Virtual Organization" by evolving the current service orientation to a higher and more business driven abstraction and (3) "Governance" of IT infrastructure.

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“…There are some other approaches, e.g. a machine learning approach to the problem is discussed in (Doan et al, 2003), and (Mitra et al, 2003) describe a probabilistic based model. Some methods tend to a trade off of different features such as efficiency and quality, as in QOM (Ehrig and Staab, 2003) and some have used approaches to integrate various similarity methods (Ehrig and Sure, 2004).…”

Section: Related Workmentioning

confidence: 99%

Coincidence Based Mapping Extraction With Genetic Algorithms

Qazvinian¹,

Abolhassani²,

Haeri³

2007

Proceedings of the Third International Conference on Web Information Systems and Technologies

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Abstract:Ontology Aligning is an answer to the problem of handling heterogenous information on different domains. After application of some measures, one reaches a set of similarity values. The final goal is to extract mappings. Our contribution is to introduce a new genetic algorithm (GA) based extraction method. The GA, employs a structured based weighting model, named "coincidence based model", as its fitness function. In the first part of the paper, some preliminaries and notations are given and then we introduce the coincidence based weighting. In the second part the paper discusses the details of the devised GA with the evaluation results for a sample dataset.

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OMEN: A Probabilistic Ontology Mapping Tool

Cited by 98 publications

References 3 publications

Managing uncertainty and vagueness in description logics for the Semantic Web

Managing uncertainty and vagueness in description logics for the Semantic Web

The IT-Socket: Model-Based Realisation of the Business and IT Alignment Framework

Coincidence Based Mapping Extraction With Genetic Algorithms

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