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Multilingual extraction and mapping of dictionary entry names in business schema integration

Published: 08 November 2010 Publication History

Abstract

Being a research field for many years, natural language processing (NLP) has gained a lot of attention in recent times due to the quality of translation software like Google Translator or Babylon. In the context of the iGreen project, we are developing a schema integration service (working title: Warp 10), which helps to generate business transformations from individual business schemata. To match the different schemas natural language processing plays an important role. Information coming from user input or files is extracted and mapped to a canonical data model (CDM) based on the CCTS standard. In this paper, we illustrate the use of NLP for the extraction of dictionary entry names (DENs) and indicate some of the problems of NLP and term extraction. Furthermore, we describe the NLP-supported mapping of DENs and outline the problems and approaches in a multilingual setting.

References

[1]
iGreen, "iGreen Project website," http://igreen-projekt.de/en_index.html, Juni. 2010.
[2]
G. Stuhec, Using CCTS Modeler Warp 10 to Customize Business Information Interfaces, Technical report, SAP AG, SAP Developer Network: Business Process Expert Community, 2007.
[3]
H. H. Do, "Schema Matching and Mapping-based Data Integration: Architecture, Approaches and Evaluation," Ph.D. Thesis, University of Leipzig, Germany, 2007.
[4]
UN/CEFACT Core Components Technical Specification Version 3.0, "UN/CEFACT Core Components Technical Specification Version 3.0," 2003.
[5]
Open Application Group, Inc. (OAGi) und American Chemistry Council's Chemical Information Technology Center (ChemITC®), "CIDX," CIDX, 2008.
[6]
P. Buitelaar, P. Cimiano, und B. Magnini, "Ontology Learning from Text: An Overview," 2003.
[7]
V. Nastase, M. Strube, B. Boerschinger, und C. Zirn, "WikiNet: A Very Large Scale Multi-Lingual Concept Network," 2010.
[8]
Richard Khoury, Fakhri Karray, und Mohamed Kamel, "Keyword extraction rules based on a part-of-speech hierarchy," International Journal of Advanced Media and Communication, Inderscience Publishers, 2008, S. pp. 138--153.
[9]
D. Weissmann, "Natural Language Processing in Automated Data Modeling," 2010.
[10]
D. Jurafsky und J. H. Martin, "Speech and Language Processing," 2009.
[11]
SAP, "SAP BusinessObjects Thingfinder," SAP Business-Objects Thinfinder, 2010.
[12]
Princeton University, "WordNet," WordNet, 2010.

Cited By

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  • (2011)A Refined Canonical Data Model for Multi-schema Integration and MappingProceedings of the 2011 IEEE 8th International Conference on e-Business Engineering10.1109/ICEBE.2011.26(105-110)Online publication date: 19-Oct-2011

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      cover image ACM Other conferences
      iiWAS '10: Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
      November 2010
      895 pages
      ISBN:9781450304214
      DOI:10.1145/1967486
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • IIWAS: International Organization for Information Integration
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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 08 November 2010

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      Author Tags

      1. Warp10
      2. iGreen
      3. natural language processing
      4. schema integration
      5. schema mapping
      6. schema modeling
      7. term extraction

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      • (2011)A Refined Canonical Data Model for Multi-schema Integration and MappingProceedings of the 2011 IEEE 8th International Conference on e-Business Engineering10.1109/ICEBE.2011.26(105-110)Online publication date: 19-Oct-2011

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