A Survey of Schema-Based Matching Approaches

Shvaiko, Pavel; Euzenat, Jérôme

doi:10.1007/11603412_5

Cited by 707 publications

(609 citation statements)

References 55 publications

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“…The problem of ontology schema mapping has been investigated by many research groups which have proposed a large variety of approaches [1,7]. While all this research has produced increasingly complex algorithms, the setting in which the mapping problem was tackled was almost always the same: given two ontologies, find all the possible mappings between their entities attaching a confidence level to the mappings that are returned.…”

Section: Mapping In the Context Of Semantic Web Toolsmentioning

confidence: 99%

“…These approaches have largely been focused on retrieving the answer from raw text 1 . An obvious hypothesis is that QA would become easier if the answers could be retrieved from semantic data.…”

Section: Motivating Scenario: Question Answering On the Semantic Webmentioning

confidence: 99%

“…Core to the information integration tasks that would be supported by SW technology are algorithms that allow matching between the elements of several, distributed ontologies. The importance of mapping for the SW has been widely recognized [1] and a range of techniques and tools have already been developed. However, the predominant view of mapping is that it will be performed at "design time", e.g.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PowerMap: Mapping the Real Semantic Web on the Fly

López

Sabou

Motta

2006

Lecture Notes in Computer Science

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Abstract. Ontology mapping plays an important role in bridging the semantic gap between distributed and heterogeneous data sources. As the Semantic Web slowly becomes real and the amount of online semantic data increases, a new generation of tools is developed that automatically find and integrate this data. Unlike in the case of earlier tools where mapping has been performed at the design time of the tool, these new tools require mapping techniques that can be performed at run time. The contribution of this paper is twofold. First, we investigate the general requirements for run time mapping techniques. Second, we describe our PowerMap mapping algorithm that was designed to be used at run-time by an ontology based question answering tool.

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Section: Mapping In the Context Of Semantic Web Toolsmentioning

confidence: 99%

Section: Motivating Scenario: Question Answering On the Semantic Webmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

PowerMap: Mapping the Real Semantic Web on the Fly

López

Sabou

Motta

2006

Lecture Notes in Computer Science

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“…These aim at discovering mappings between the entities of schemas/ontologies which correspond semantically to each other, see [23,24]. Mappings are typically specified (i) by using coefficients rating match quality in the [0,1] range, see [5,10,20,30], or (ii) by using logical relations (e.g., equivalence, subsumption), see [11,12].…”

Section: Knowledge Processing Tasks and Componentsmentioning

confidence: 99%

On Identifying Knowledge Processing Requirements

Léger

Nixon

Shvaiko

2005

The Semantic Web – ISWC 2005

Self Cite

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Abstract. The uptake of Semantic Web technology by industry is progressing slowly. One of the problems is that academia is not always aware of the concrete problems that arise in industry. Conversely, industry is not often well informed about the academic developments that can potentially meet its needs. In this paper we present a first step towards a successful transfer of knowledge-based technology from academia to industry. In particular, we present a collection of use cases from enterprises which are interested in Semantic Web technology. We provide a detailed analysis of the use cases, identify their technology locks, discuss the appropriateness of knowledge-based technology and possible solutions. We summarize industrial knowledge processing requirements in the form of a typology of knowledge processing tasks and a library of high level components for realizing those tasks. Eventually these results are intended to focus academia on the development of plausible knowledge-based solutions for concrete industrial problems, and therefore, facilitate the uptake of Semantic Web technology within industry.

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“…Overviews of approaches for ontology matching in general are given in [18,10,2,20]. Typically, matching utilizes metadata, associated instances or both.…”

Section: Related Workmentioning

confidence: 99%

Instance-Based Matching of Large Life Science Ontologies

Kirsten

Thor

Rahm

Lecture Notes in Computer Science

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Abstract.Ontologies are heavily used in life sciences so that there is increasing value to match different ontologies in order to determine related conceptual categories. We propose a simple yet powerful methodology for instance-based ontology matching which utilizes the associations between molecular-biological objects and ontologies. The approach can build on many existing ontology associations for instance objects like sequences and proteins and thus makes heavy use of available domain knowledge. Furthermore, the approach is flexible and extensible since each instance source with associations to the ontologies of interest can contribute to the ontology mapping. We study several approaches to determine the instance-based similarity of ontology categories. We perform an extensive experimental evaluation to use protein associations for different species to match between subontologies of the Gene Ontology and OMIM. We also provide a comparison with metadata-based ontology matching.

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A Survey of Schema-Based Matching Approaches

Cited by 707 publications

References 55 publications

PowerMap: Mapping the Real Semantic Web on the Fly

PowerMap: Mapping the Real Semantic Web on the Fly

On Identifying Knowledge Processing Requirements

Instance-Based Matching of Large Life Science Ontologies

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