Ontology generation from tables

Tijerino, Yuri A.; Embley, David W.; Lonsdale, Deryle; Nagy, George

doi:10.1109/wise.2003.1254487

Cited by 25 publications

(35 citation statements)

References 19 publications

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“…To interpret table structures, previous works make use of prior knowledge such as types of tables determined by examining similarity of data [2,13] and the cognition model of tables [11]. Domainspecific knowledge bases are also used [6,12]. The aim of these previous works is to extract relations between data from tables in a specific domain automatically.…”

Section: Cover Tables In Various Domainsmentioning

confidence: 99%

Ontology extraction from tables on the Web

Tanaka

Ishida

2006

International Symposium on Applications and the Internet (SAINT'06)

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Section: Cover Tables In Various Domainsmentioning

confidence: 99%

Ontology extraction from tables on the Web

Tanaka

Ishida

2006

International Symposium on Applications and the Internet (SAINT'06)

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“…The first step of TANGO [2] is to convert a physical table to a layout independent (abstract) form that can be used to create ontologies. This paper describes the Wang Notation Tool (WNT), a semi-automatic tool to convert HTML tables to layout independent Wang notation [3].…”

Section: Introductionmentioning

confidence: 99%

Wang Notation Tool: Layout independent representation of tables

Jha

Nagy

2008

2008 19th International Conference on Pattern Recognition

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“…While understanding context in a natural language setting is difficult, structured information such as tables 1 makes it easier to interpret new items and relations. We organize the new knowledge we gain from "understanding" tables as an ontology and thus we call our information-gathering engine TANGO (Table ANalysis for Generating Ontologies) [45].…”

Section: Introductionmentioning

confidence: 99%

Towards Ontology Generation from Tables

et al. 2005

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At the heart of today's information-explosion problems are issues involving semantics, mutual understanding, concept matching, and interoperability. Ontologies and the Semantic Web are offered as a potential solution, but creating ontologies for real-world knowledge is nontrivial. If we could automate the process, we could significantly improve our chances of making the Semantic Web a reality. While understanding natural language is difficult, tables and other structured information make it easier to interpret new items and relations. In this paper we introduce an approach to generating ontologies based on table analysis. We thus call our approach TANGO (Table ANalysis for Generating Ontologies). Based on conceptual modeling extraction techniques, TANGO attempts to (i) understand a table's structure and conceptual content; (ii) discover the constraints that hold between concepts extracted from the table; (iii) match the recognized concepts with ones from a more general specification of related concepts; and (iv) merge the resulting structure with other similar knowledge representations. TANGO is thus a formalized method of processing the format and content of tables that can serve to incrementally build a relevant reusable conceptual ontology.

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Ontology generation from tables

Cited by 25 publications

References 19 publications

Ontology extraction from tables on the Web

Ontology extraction from tables on the Web

Wang Notation Tool: Layout independent representation of tables

Towards Ontology Generation from Tables

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