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Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.


Papers
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Journal ArticleDOI
TL;DR: An ontology learning and population system that combines both statistical and semantic methodologies is presented that achieves good performances on standard datasets.
Abstract: The success of Semantic Web will heavily rely on the availability of formal ontologies to structure machine understanding data. However, there is still a lack of general methodologies for ontology automatic learning and population, i.e. the generation of domain ontologies from various kinds of resources by applying natural language processing and machine learning techniques In this paper, the authors present an ontology learning and population system that combines both statistical and semantic methodologies. Several experiments have been carried out, demonstrating the effectiveness of the proposed approach. HighlightsA graph of terms can be effectively used for ontology building.Such a graph is extracted from documents thanks to a LDA based methodology.Ontology learning involves the use of annotated lexicons (WordNet).Proposed method achieves good performances on standard datasets.

46 citations

Journal ArticleDOI
TL;DR: An automated method to construct the domain ontology by calculating a TF-IDF to find the weight of terms, using a recursive ART network to cluster terms, and outputs an ontology in a Jena package using an RDF format is proposed.
Abstract: Ontology describes data about data and offers a group of glossaries with a definition that encompasses them in their entire. It not only transfers syntax of words but also accurately transfers semantic data between human users and the network. Hence, the usefulness of the semantic web depends on whether the domain ontology can be constructed effectively and correctly. In this paper we propose an automated method to construct the domain ontology. First, we collected domain-related web pages from the Internet. Secondly, we use the HTML tag labels to choose meaningful terms from the web pages. Next, we use these terms to construct the domain ontology by calculating a TF-IDF to find the weight of terms, using a recursive ART network (Adaptive Resonance Theory Network) to cluster terms. Each group of terms will find a candidate keyword for ontology construction. Boolean operations locate individual keywords in a hierarchy. Finally, the system outputs an ontology in a Jena package using an RDF format. The primary experiment indicates that our method is useful for domain ontology creation.

46 citations

01 Jan 2010
TL;DR: Preliminary evaluation results indicate the promise of the cross- lingual mapping approach used in the SOCOM framework, and suggest that the integrated appropriate ontology label translation mechanism is effective in the facilitation of monolingual matching techniques in cross-lingual ontology mapping scenarios.
Abstract: knowledge management systems enable the automatic discovery, sharing and reuse of structured data sources on the semantic web. With the emergence of multilingual ontologies, accessing knowledge across natural language barriers has become a pressing issue for the multilingual semantic web. In this paper, a semantic-oriented cross-lingual ontology mapping (SOCOM) framework is proposed to enhance interoperability of ontology-based systems that involve multilingual knowledge repositories. The contribution of cross-lingual ontology mapping is demonstrated in two use case scenarios. In addition, the notion of appropriate ontology label translation, as employed by the SOCOM framework, is examined in a cross-lingual ontology mapping experiment involving ontologies with a similar domain of interest but labelled in English and Chinese respectively. Preliminary evaluation results indicate the promise of the cross- lingual mapping approach used in the SOCOM framework, and suggest that the integrated appropriate ontology label translation mechanism is effective in the facilitation of monolingual matching techniques in cross-lingual ontology mapping scenarios.

46 citations

Journal ArticleDOI
TL;DR: This work proposes a general theory that uses a syntax- and interpretation-independent formulation of language, ontology, and ontological commitment in terms of institutions and claims that its formalisation generalises the intuitive notion of ontology-based semantic integration while retaining its basic insight.
Abstract: We address what is still a scarcity of general mathematical foundations for ontology-based semantic integration underlying current knowledge engineering methodologies in decentralised and distributed environments. After recalling the first-order ontology-based approach to semantic integration and a formalisation of ontological commitment, we propose a general theory that uses a syntax- and interpretation-independent formulation of language, ontology, and ontological commitment in terms of institutions. We claim that our formalisation generalises the intuitive notion of ontology-based semantic integration while retaining its basic insight, and we apply it for eliciting and hence comparing various increasingly complex notions of semantic integration and ontological commitment based on differing understandings of semantics.

46 citations

Patent
05 May 2005
TL;DR: In this article, an upper ontology of predefined concept and relationship types, and a predefined set or relationships that may be used to connect particular pairs of concepts is presented.
Abstract: The invention relates to the structure of an upper ontology and a system and method for utilizing an upper ontology in the creation of one or more multi-relational ontologies. The invention includes an upper ontology of predefined concept and relationship types, and a predefined set or relationships that may be used to connect particular pairs of concepts. The concept and relationship types may be dictated by the knowledge domains in which the resultant ontology is to reside. The invention may also include a hierarchy of concept types wherein the relationships that may exist between concept types is specified.

46 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202337
2022149
202111
202011
201919
201843