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Progress in Computing, Analytics and Networking pp 295–304Cite as

Identifying Dissimilar OLAP Query Session for Building Goal Hierarchy

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 710))

Abstract

Traditionally, a goal-oriented approach follows the goal decomposition technique to build a goal hierarchy in order to identify the schema for a data warehouse. In our earlier work, using reverse engineering approach, a goal hierarchy was built for an existing data warehouse schema using a single query session. The tasks of this hierarchy address some part of the warehouse. In this paper, we address the issue of identifying the next session to build a goal hierarchy. The sessions which provide the tasks and information goals distinct from existing goal hierarchy are desirable. To identify such a session, we define distance between sessions. The session whose distance from the current session is maximum is picked up.

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References

  1. Inmon, W.H.: Building the data warehouse. 4th edn. Wiley Publishing Inc, USA (1992).

    Google Scholar 

  2. Mazón, J.N., Pardillo, J., Trujillo, J.: A model-driven goal-oriented requirement engineering approach for data warehouses. In: ER Workshops 2007, LNCS, vol. 4802, pp. 255–264. Springer, Heidelberg (2007).

    Google Scholar 

  3. Salinesi, C., Gam, I.: A requirement-driven approach for designing data warehouses. In: Requirements Engineering: Foundations for Software Quality (REFSQ”06), p. 1. Luxembourg (2006).

    Google Scholar 

  4. Giorgini, P., Rizzi, S., Garzetti, M.: Goal-oriented requirement analysis for data warehouse design. In: Proceedings of the 8th ACM international workshop on Data warehousing and OLAP (DOLAPʹ05), pp. 47–56. Germany (2005).

    Google Scholar 

  5. Giorgini, P., Rizzi, S., Garzetti, M. (2008): GRAnD: A goal-oriented approach to requirement analysis in data warehouses. Decision Support Systems, vol. 45, no. 1, 4–21 (2005).

    Google Scholar 

  6. Golfarelli, M., Maio, D., Rizzi, S.: The dimensional fact model: a conceptual model for data warehouses. International Journal of Cooperative Information Systems, 7(02n03), 215–247 (1998).

    Google Scholar 

  7. Ranjan R.K., Parimala N.: A bottom-up approach for creating goal hierarchy using olap query recommendation technique, Int. J. Business Information Systems (Accepted 2017).

    Google Scholar 

  8. Aligon, J., Gallinucci, E., Golfarelli, M., Marcel, P., Rizzi, S.: A collaborative filtering approach for recommending olap sessions. Decision Support Systems, 69, 20–30 (2015).

    Google Scholar 

  9. Jensen, M., Holmgren, T., Pedersen, T.: Discovering multidimensional structure in relational data. In: Proceedings of International Conference on Data Warehousing and Knowledge Discovery, pp. 138–148. Zaragoza, Spain (2004).

    Google Scholar 

  10. Prakash, N., Gosain, A.: Requirements driven data warehouse development. CAiSE Short Paper Proceedings, Vol. 252. Springer (2003).

    Google Scholar 

  11. Parimala, N., Ranjan, R.K.: Mapping extended rationale diagrams to olap queries. ACM SIGSOFT Software Engineering Notes, vol. 38, no. 3, 1–6 (2013).

    Google Scholar 

  12. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 6, 734–749 (2005).

    Google Scholar 

  13. Aligon, J., Golfarelli, M., Marcel, P., Rizzi, S., Turricchia, E.: Mining preferences from olap query logs for proactive personalization. In: Proceedings ADBIS, pp. 84–97. Vienna, Austria, (2011).

    Google Scholar 

  14. Jerbi, H., Ravat, F., Teste, O., Zurfluh, G.: Preference-based recommendations for olpa analysis. In: Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery (DaWaKʹ09), pp. 467–478. Springer-Verlag, Berlin, Heidelberg (2009).

    Google Scholar 

  15. Giacometti, A., Marcel, P., Negre, E.: A framework for recommending olap queries. In: Proceedings of the ACM 11th international workshop on Data warehousing and OLAP, pp. 73–80. ACM (2008).

    Google Scholar 

  16. Aissa, S., Gouider, M.S.: A new similairty measure for spatial personalization. International Journal of Database Management System, vol. 4, no. 4, 1–12 (2012).

    Google Scholar 

  17. Aligon, J., Golfarelli, M., Marcel, P., Rizzi, S., Turricchia, E.: Similarity measures for olap sessions. Knowledge and Information Systems, 39(2), 463–489 (2014).

    Google Scholar 

  18. Smith, B., Clay, C.: Microsoft sql server 2008 mdx step by step. Pearson Education, Washington, USA (2009).

    Google Scholar 

  19. Microsoft SQL Server 2012. https://www.microsoft.com/en-in/download/details.aspx?id=29062, last accessed 2016/08/01.

  20. AdventureWorksDW: Microsoft sql server. https://msftdbprodsamples.codeplex.com, last accessed 2016/08/01.

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Acknowledgements

This research was supported by Department of Science and Technology, Govt. of India, under the project “DST-PURSE Program, Phase- II”.

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Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    N. Parimala & Ranjeet Kumar Ranjan

Authors
  1. N. Parimala
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  2. Ranjeet Kumar Ranjan
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Correspondence to Ranjeet Kumar Ranjan .

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Editors and Affiliations

  1. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  2. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Siddharth Swarup Rautaray

  3. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Himansu Das

  4. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

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Parimala, N., Ranjan, R.K. (2018). Identifying Dissimilar OLAP Query Session for Building Goal Hierarchy. In: Pattnaik, P., Rautaray, S., Das, H., Nayak, J. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-7871-2_29

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  • DOI: https://doi.org/10.1007/978-981-10-7871-2_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7870-5

  • Online ISBN: 978-981-10-7871-2

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