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A Text Mining Approach to Integrating Business Process Models and Governing Documents

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On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops (OTM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3762))

Abstract

As large companies are building up their enterprise architecture solutions, they need to relate business process descriptions to lengthy and formally structured documents of corporate policies and standards. However, these documents are usually not specific to particular tasks or processes, and the user is left to read through a substantial amount of irrelevant text to find the few fragments that are relevant to him. In this paper, we describe a text mining approach to establishing links between business process model elements and relevant parts of governing documents in Statoil, one of Norway’s largest companies. The approach builds on standard IR techniques, gives us a ranked list of text fragments for each business process activity, and can easily be integrated with Statoil’s enterprise architecture solution. With these ranked lists at hand, users can easily find the most relevant sections to read before carrying out their activities.

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References

  1. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. Addison-Wesley, Reading (1999)

    Google Scholar 

  2. Conklin, J.: A survey of hypertext. Technical Report 2, Austin, Texas, 3 (1987)

    Google Scholar 

  3. Decker, S., Erdmann, M., Fensel, D., Studer, R.: Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information. Kluwer Academic Publisher, Boston (1999)

    Google Scholar 

  4. Engels, R., Lech, T.: Towards the Semantic Web: Ontology-Driven Knowledge Management. In: Generating Ontologies for the Semantic Web: OntoBuilder. John Wiley & Sons, Chichester (2003)

    Google Scholar 

  5. Fensel, D., van Harmelen, F., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F.: Oil: An ontology infrastructure for the semantic web. IEEE Intelligent Systems 16(2), 38–45 (2001)

    Article  Google Scholar 

  6. Handschuh, S., Staab, S., Maedche, A.: Creating relational metadata (cream) - a framework for semantic annotation. In: The Emerging Semantic Web (2001)

    Google Scholar 

  7. Heflin, J., Hendler, J.: Searching the web with shoe (2000)

    Google Scholar 

  8. Ingvaldsen, J.E., Gulla, J.A., Hegle, O.A., Prange, A.: Revealing the real business flows from enterprise systems transactions. In: Accepted for publication, 7th International Conference on Enterprise Information Systems (2005)

    Google Scholar 

  9. Maedche, A., Schnurr, H.p., Erdmann, M., Staab, S.: From manual to semi-automatic semantic annotation: About ontology-based text annotation tools (June 23 2000)

    Google Scholar 

  10. Maedche, A., Staab, S.: Mining ontologies from text. In: Dieng, R., Corby, O. (eds.) EKAW 2000. LNCS (LNAI), vol. 1937, pp. 189–202. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  11. Maedche, E., Staab, S.: Ontology learning for the semantic web (February 08 2001)

    Google Scholar 

  12. Martin, P., Eklund, P.: Embedding knowledge in Web documents: CGs versus XML-based metadata languages. In: Tepfenhart, W.M. (ed.) ICCS 1999. LNCS, vol. 1640, pp. 230–246. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  13. Miller, G.: WordNet: an online lexical database. International Journal of Lexicography 3(4) (1990)

    Google Scholar 

  14. Missikoff, M., Navigli, R., Velardi, V.: The usable ontology: An environment for building and assessing a domain ontology. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 39–53. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  15. Navigli, R., Velardi, P., Gangemi, A.: Ontology learning and its application to automated terminology translation. IEEE Intelligent Systems 18(1), 22–31 (2003)

    Article  Google Scholar 

  16. Scheer, A.-W., Nüttgens, M.: ARIS architecture and reference models for business process management. In: van der Aalst, W.M.P., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, pp. 376–389. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  17. Su, X., Gulla, J.A.: Semantic enrichment for ontology mapping. In: Meziane, F., Métais, E. (eds.) NLDB 2004. LNCS, vol. 3136, pp. 217–228. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

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Ingvaldsen, J.E., Gulla, J.A., Su, X., Rønneberg, H. (2005). A Text Mining Approach to Integrating Business Process Models and Governing Documents. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops. OTM 2005. Lecture Notes in Computer Science, vol 3762. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575863_67

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  • DOI: https://doi.org/10.1007/11575863_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29739-0

  • Online ISBN: 978-3-540-32132-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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