Ontology Mapping: An Information Retrieval and Interactive Activation Network Based Approach

Mao, Ming

doi:10.1007/978-3-540-76298-0_72

Cited by 23 publications

(15 citation statements)

References 12 publications

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“…Profile Similarity Given two ontology concepts, one can determine their similarity by creating their respective virtual documents, in the literature also referred to as profiles [24,41], and applying a document similarity metric [62]. Hence, the applied metric can be treated as a concept similarity and directly integrated into a ontology mapping system.…”

Section: Virtual Documents In Ontology Mappingmentioning

confidence: 99%

Word-Sense Disambiguation for Ontology Mapping: Concept Disambiguation using Virtual Documents and Information Retrieval Techniques

Schadd

Roos

2014

J Data Semant

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Ontology mapping is a crucial task for the facilitation of information exchange and data integration. A mapping system can use a variety of similarity measures to determine concept correspondences. This paper proposes the integration of word-sense disambiguation techniques into lexical similarity measures. We propose a disambiguation methodology which entails the creation of virtual documents from concept and sense definitions, including their neighbourhoods. The specific terms are weighted according to their origin within their respective ontology. The document similarities between the concept document and sense documents are used to disambiguate the concept meanings. First, we evaluate to what extent the proposed disambiguation method can improve the performance of a lexical similarity metric. We observe that the disambiguation method improves the performance of each tested lexical similarity metric. Next, we demonstrate the potential of a mapping system utilizing the proposed approach through the comparison with contemporary ontology mapping systems. We observe a high performance on a real-world data set. Finally, we evaluate how the application of several term-weighting techniques on the virtual documents can affect the quality of the generated alignments. Here, we observe that weighting terms according to their ontology origin leads to the highest performance.

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Section: Virtual Documents In Ontology Mappingmentioning

confidence: 99%

Word-Sense Disambiguation for Ontology Mapping: Concept Disambiguation using Virtual Documents and Information Retrieval Techniques

Schadd

Roos

2014

J Data Semant

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“…In IR, ontology can be used on various levels [5], [9], [10]. First, it makes it possible to refine a system based on a traditional process of indexing by increasing the chances to formulate a request starting from the terms or descriptors representing as well as possible information requirements.…”

Section: Ontology-based Information Retrievalmentioning

confidence: 99%

Ontology-based information retrieval for e-Learning of computer science

Ahmed-Ouamer

Hammache

2010

2010 International Conference on Machine and Web Intelligence

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Nowadays, resources on the web increase considerably. In this immense data warehouse, current information retrieval systems do not allow users to obtain results to their requests that meet exactly their needs. Mainly this is due to indexing techniques used (key words, thesaurus). In order to improve the relevance of information retrieval, an ontology-based approach called OBIREX is proposed in this paper. OBIREX is based on the use of ontology of the domain for indexing a collection of documents and the use of semantic links between documents to allow the inference of all relevant documents. This approach is tested on the domain of e-learning of computer science in the context of the semantic web. Some results obtained are also presented.

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“…There are some methods about ontology mapping currently, such as FCA-Mapping, automatic ontology mapping method realized by the combination of cognitive supportive theory and decision-making [23], ontology mapping method accomplished by the combination of distance feature of standard string and similarity measurement of results based with vector performance [24], ontology mapping method base on OCL [25], method base on information retrieval and mutual active net [26], etc.…”

Section: Organization Of Multilingual Resourcementioning

confidence: 99%

Discussion about automatically organizing network education resources with multilingual thesauri-ontology

Deng

Liu

2009

2009 IEEE International Symposium on IT in Medicine &Amp; Education

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The types and the ways to organizing network education resources are surveyed. The multilingual thesaurus-ontology is explained. Then it discusses application of multilingual thesaurus-ontology in the organization of network education resources. The purpose of the application is to make network education resources maintain automatically, by the characteristic of self-learning and auto-evolution of thesaurus-ontology.

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Ontology Mapping: An Information Retrieval and Interactive Activation Network Based Approach

Cited by 23 publications

References 12 publications

Word-Sense Disambiguation for Ontology Mapping: Concept Disambiguation using Virtual Documents and Information Retrieval Techniques

Word-Sense Disambiguation for Ontology Mapping: Concept Disambiguation using Virtual Documents and Information Retrieval Techniques

Ontology-based information retrieval for e-Learning of computer science

Discussion about automatically organizing network education resources with multilingual thesauri-ontology

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