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Information Logistics in Engineering Change Management: Integrating Demand Patterns and Recommendation Systems

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 106))

Abstract

During the last decade, manufacturing industries experienced a shift towards networked organisation structures. In such organizations, engineering change management is a complex process aiming at implementing required changes in the product timely, completely and by including all affected and involved partners. Information demand patterns have been proposed as a way of capturing organizational knowledge regarding the information flow for such change management processes. This paper aims at extending this work by investigating approaches from group recommendation systems for implementing IT-support of the pattern use. The paper presents an approach for integration information demand patterns and recommendation systems, an architecture for recommendation systems and a clustering approach.

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References

  1. Baatarjav, E.-A., Phithakkitnukoon, S., Dantu, R.: Group Recommendation System for Facebook. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM-WS 2008. LNCS, vol. 5333, pp. 211–219. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  2. Chen, Y.-J., Chen, Y.-M., Wu, M.-S.: An expert recommendation system for product empirical knowledge consultation. In: 3rd IEEE International Conference on Computer Science and Information Technology, pp. 23–27. IEEE Press, New York (2010)

    Chapter  Google Scholar 

  3. CMII Research Institute: CMII Standard for Product Configuration Management. Document CMII-105C, www.cmiiresearch.com (accessed on February 4, 2010)

  4. Deiters, W., Löffeler, T., Pfenningschmidt, S.: The Information Logistical Approach Toward a User Demand-driven Information Supply. In: Cross-Media Service Delivery, pp. 37–48. Kluwer Academic Publisher (2003)

    Google Scholar 

  5. Flake, G.W., Lawrence, S., Giles, C.L., Coetzee, F.: Self-Organization and identification of Web Communities. IEEE Computer 35(3), 66–71 (2002)

    Article  Google Scholar 

  6. Garcia, I., Sebastia, L., Onaindia, E., Guzman, C.: A Group Recommender System for Tourist Activities. In: Di Noia, T., Buccafurri, F. (eds.) EC-Web 2009. LNCS, vol. 5692, pp. 26–37. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  7. Hornung, T., Koschmider, A., Oberweis, A.: A Recommender System for Business Process Models. In: Proceedings of the 17th Annual Workshop on Information Technologies & Systems (2009), http://ssrn.com/abstract=1328244

  8. Jaksch, S., Pfennigschmidt, S., Sandkuhl, K., Thiel, C.: Information Logistic Applications for Information-on-Demand Scenarios: Concepts and Experiences from WIND Project. In: 29th Euromicro Conference, Antalya, Turkey, pp. 141–147. IEEE Press, New York (2003)

    Google Scholar 

  9. Kotinurmi, P.: User Profiles and Their Management (2001), http://www.tml.tkk.fi/Studies/Tik-111.590/2001s/papers/paavo_kotinurmi.pdf

  10. Lundqvist, M.: Context as a Key Concept in Information Demand Analysis. In: Doctoral Consortium Associated with the 5th Intl. and Interdisciplinary Conference on Modelling and Using Context, Paris, France, pp. 63–73 (2005)

    Google Scholar 

  11. Lundqvist, M., Sandkuhl, K., Seigerroth, U.: Modelling Information Demand in an Enterprise Context: Method, Notation and Lessons Learned. IJISMD 2(3), 74–96 (2011)

    Google Scholar 

  12. McCarthy, K., Salamo, M., Coyole, L., McGinty, L., Smyth, B., Nixon, P.: Group Recommender Systems: A Critiquing Based Approach. In: 11th International Conference on Intelligent User Interfaces, pp. 267–269. ACM Press (2006)

    Google Scholar 

  13. Meissen, U., Pfennigschmidt, S., Voisard, A., Wahnfried, T.: Context- and Situation-Awareness in Information Logistics. In: Lindner, W., Fischer, F., Türker, C., Tzitzikas, Y., Vakali, A.I. (eds.) EDBT 2004. LNCS, vol. 3268, pp. 335–344. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  14. Middleton, S.E., De Roure, D., Shadbolt, N.R.: Ontology-Based Recommender Systems. In: Staab, S., Rudi, S. (eds.) Handbook on Ontologies, International Handbooks on Information Systems, pp. 477–498. Springer, Heidelberg (2003)

    Google Scholar 

  15. Moon, S.K., Simpson, T.W., Kumara, S.R.T.: An Agent-Based Recommender System for Developing Customized Families of Products. Journal of Intelligent Manufacturing 20(6), 649–659 (2009)

    Article  Google Scholar 

  16. Petrusel, R., Mican, D.: Mining Decision Activity Logs. In: Abramowicz, W., Tolksdorf, R., Węcel, K. (eds.) BIS 2010. LNBIP, vol. 57, pp. 67–79. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  17. Romesburg, H.C.: Cluster Analysis for Researchers. Lulu Press, California (2004)

    Google Scholar 

  18. Rozinat, A., van der Aalst, W.M.P.: Decision Mining in Business Processes, BPM Center Report no. BPM-06-10 (2006)

    Google Scholar 

  19. Sandkuhl, K.: Improving Engineering Change Management with Information Demand Patterns. In: 8th International Conference on Product Lifecycle Management, Eindhoven, The Netherlands. Inderscience Enterprises (2011)

    Google Scholar 

  20. Setten, M., Veenstra, M., Nijholt, A.: Prediction Strategies: Combining Prediction Techniques to Optimize Personalization. In: 2nd Workshop on Personalization in Future TV, Malaga, Spain (2002)

    Google Scholar 

  21. Smirnov, A., Pashkin, M., Chilov, N.: Personalized Customer Service Management for Networked Enterprises. In: 11th International Conference on Concurrent Enterprising, pp. 295–302 (2005)

    Google Scholar 

  22. Smirnov, A., Pashkin, M., Levashova, T., Kashevnik, A., Shilov, N.: Context-Driven Decision Mining. In: Encyclopedia of Data Warehousing and Mining, Information Science Preference, 2nd edn., Hershey, New York, vol. 1, pp. 320–327 (2008)

    Google Scholar 

  23. Tan, P.-N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison Wesley (2005)

    Google Scholar 

  24. Zhena, L., Huangb, G.Q., Jiang, Z.: Recommender System Based on Workflow. Decision Support Systems 48(1), 237–245 (2009)

    Article  Google Scholar 

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Sandkuhl, K., Smirnov, A., Shilov, N. (2012). Information Logistics in Engineering Change Management: Integrating Demand Patterns and Recommendation Systems. In: Niedrite, L., Strazdina, R., Wangler, B. (eds) Workshops on Business Informatics Research. BIR 2011. Lecture Notes in Business Information Processing, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29231-6_2

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  • DOI: https://doi.org/10.1007/978-3-642-29231-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29230-9

  • Online ISBN: 978-3-642-29231-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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