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OntoNaviERP: Ontology-supported Navigation in ERP Software  Documentation
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This presentation explains how ontologies and automated annotation techniques can improve users\' access to SAP help documentation. The original talk was given at ISWC 2008; for the full paper, see ...

This presentation explains how ontologies and automated annotation techniques can improve users\' access to SAP help documentation. The original talk was given at ISWC 2008; for the full paper, see http://dblp.uni-trier.de/rec/bibtex/conf/semweb/HeppW08 or http://www.heppnetz.de/publications/.

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OntoNaviERP: Ontology-supported Navigation in ERP Software Documentation Presentation Transcript

  • 1. OntoNaviERP: Ontology-supported Navigation in ERP Software Documentation Martin Hepp1,2 and Andreas Wechselberger1 1E-Business and Web Science Research Group, Bundeswehr University Munich, Germany 2STI Innsbruck, Austria {mhepp@computer.org | andreas.wechselberger@unibw.de} Martin Hepp 1 mhepp@computer.org
  • 2. ERP: Enterprise Resource Planning MRP: Material Requirements Planning MRP-II: Manufacturing Resource Planning CIM: Computer Integrated Comprehensive --> Manufacturing Complex Martin Hepp 2 mhepp@computer.org
  • 3. SAP Help Files Martin Hepp 3 mhepp@computer.org
  • 4. Search is important, because ... • Users must align their mental models of processes and data with those underlying the ERP Document ? Function software Role Event • Intensive usage Function • More efficient usage of ERP documentation means more efficient business operations. Martin Hepp 4 mhepp@computer.org
  • 5. Search is difficult, because ... Martin Hepp 5 mhepp@computer.org
  • 6. Search is difficult, because ... Martin Hepp 5 mhepp@computer.org
  • 7. Search is difficult, because ... Textbook Business Terminology SAP Business SAP IT/System Terminology Terminology Industry Domain Terminology Martin Hepp 5 mhepp@computer.org
  • 8. In other words: An ideal showcase for semantic technology... Martin Hepp 6 mhepp@computer.org
  • 9. Requirements • Cost-efficient Ontology Construction • Cost-efficient Annotation • Speed • User Interface Martin Hepp 7 mhepp@computer.org
  • 10. Competency Question Martin Hepp 8 mhepp@computer.org
  • 11. Overview: OntoNaviERP Martin Hepp 9 mhepp@computer.org
  • 12. Which Terms Are Most Valuable - The Most Popular, the Frequent, or the Rare? Frequency vs. Information Value vs. Likelihood of Relevance Web-wide Number of Occurrences + Likelihood of relevant documents + Likelihood of usage in queries - limited information value balance between frequency and specificity + higher information value + highest information value if needed - likelihood of occurrence in query low - likelihood of relevant documents low Term 1..N (similar pattern for: Tags, Ontology Elements) Martin Hepp 10 mhepp@computer.org
  • 13. Approach: Conceptual Model Martin Hepp 11 mhepp@computer.org
  • 14. Approach: Conceptual Model Semi-automatically Traditional derived from ontology term lists engineering Martin Hepp 11 mhepp@computer.org
  • 15. Approach: Ontology Construction (1) • Script • Protégé • WordNet Plug-In • OWL Annotation Property • .NT Generator Martin Hepp 12 mhepp@computer.org
  • 16. Approach: Ontology Construction (2) Martin Hepp 13 mhepp@computer.org
  • 17. Approach: Ontology Construction (3) 5 * 127 = 635 126 * 257 = 32,382 Martin Hepp 14 mhepp@computer.org
  • 18. Approach: Annotation (1) Martin Hepp 15 mhepp@computer.org
  • 19. Approach: Annotation (2) Martin Hepp 16 mhepp@computer.org
  • 20. Approach: User Interface and System Martin Hepp 17 mhepp@computer.org
  • 21. Evaluation Methodology Martin Hepp 18 mhepp@computer.org
  • 22. Results (1) Median of retrieved documents • Term-based: 0 >=50% of the action-topic pairs yield no result • OntoNaviERP: 5.5 50% of of the action-topic pairs return at least 5 result pages, of which 2 are relevant Martin Hepp 19 mhepp@computer.org
  • 23. Results (2) Martin Hepp 20 mhepp@computer.org
  • 24. Findings and Lessons Learned • Understanding of ontology engineering and annotation under economic constraints • In our setting, consolidation of synonyms and lexical variants does a great deal of the job Martin Hepp 21 mhepp@computer.org
  • 25. Future Extensions • Task and Context • Annotate individual sections of resources • Skills / Users’ Competencies vs. Target Audience of a Resource • Hybrid Search: Combining term-based and conceptual search E.g. see Bhagdev/Chapman/Ciravegna, Vitaveska Lanfranchi, Daniela Petrelli: Hybrid Search: Effectively Combining Keywords and Semantic Searches, ESWC 2008 Martin Hepp 22 mhepp@computer.org
  • 26. Reference and Links Hepp, Martin and Wechselberger, Andreas: OntoNaviERP: Ontology- supported Navigation in ERP Software Documentation, in: A. Sheth et al. (eds.): ISWC 2008. Proceedings of the 7th International Semantic Web Conference, Germany, October 26-30, 2008, Karlsruhe, Germany, Springer LNCS, Vol. 5318, pp. 764-776. This paper and other papers are available at http://www.heppnetz.de/publications/ The .NT Generator for KIM/GATE Gazetteer Lists is at: http://ebusiness-unibw.org:8180/ntfilegenerator/ Martin Hepp 23 mhepp@computer.org
  • 27. Thank you! Martin Hepp and Andreas Wechselberger {mhepp@computer.org | andreas.wechselberger@unibw.de} http://www.unibw.de/ebusiness/ Martin Hepp 24 mhepp@computer.org