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Labelling Business Entities in a Canonical Data Model

  • Enterprises express the concepts of their electronic business-to-business (B2B) communication in individual ontology-like schemas. Collaborations require merging schemas’ common concepts into Business Entities (BEs) in a Canonical Data Model (CDM). Although consistent, automatic schema merging is state of the art, the task of labeling the BEs with descriptive, yet short and unique names, remains. Our approach first derives a heuristically ranked list of candidate labels for each BE locally from the names and descriptions of the underlying concepts. Second, we use constraint satisfaction to assign a semantically unique name to each BE that optimally distinguishes it from the other BEs. Our system’s labels outperform previous work in their description of BE content and in their discrimination between similar BEs. In a task-based evaluation, business experts estimate that our approach can save about 12% of B2B integration effort compared to previous work and about 49% in total.

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  • Main Conference Proceedings of the 12th Konvens 2014

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Author:Nathali Ortiz Suarez, Jens Lemcke, Ulrike Pado
Parent Title (English):Proceedings of the 12th edition of the KONVENS conference
Document Type:Conference Proceeding
Date of Publication (online):2014/10/23
Release Date:2014/10/23
Information Extraction
GND Keyword:Computerlinguistik
First Page:158
Last Page:164
PPN:Link zum Katalog
Contributor:Faaß, Gertrud
Institutes:Fachbereich III / Informationswissenschaft und Sprachtechnologie
DDC classes:400 Sprache / 400 Sprache, Linguistik
Collections:KONVENS 2014 / Proceedings of the 12th KONVENS 2014
Licence (German):License LogoCreative Commons - Namensnennung 3.0