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Encyclopedia of Database Systems pp 2550–2555Cite as

OLAP Personalization and Recommendation

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Definition

Personalizing or recommending OLAP queries aims at making the OLAP user experience less disorientating when navigating huge amounts of multidimensional data (also called cubes). Such approaches allow coping with too many or too few query results, or suggesting new queries to pursue the navigation. Personalization allows adding preferences to a query for filtering out irrelevant results or ranking the results to focus on the most relevant first. It also allows turning selection predicates (hard constraints) into preferences (soft constraints) to favor nonempty answers. On the other end, recommendation allows to leverage the cube instance and/or past navigations on it to complement the current query result.

The general problem can be formally defined by given a sequence of queries S = <q1, …, qc> (a session from now on) over an instance I of a cube schema C, a user profile P(consisting of ordered multidimensional objects), and a set of past sessions L (a log from now on),...

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Recommended Readings

  1. Aligon J, Similarity based recommendation of OLAP sessions, doctoral dissertation, Université François Rabelais Tours, France; 2013.

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  2. Aligon J, Golfarelli M, Marcel P, Rizzi S, Turricchia E. Mining preferences from OLAP query logs for proactive personalization. In: Proceedings of the 15th East European Conference on Advances in Databases and Information Systems; 2011. p. 84–97.

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  3. Aligon J, Golfarelli M, Marcel P, Rizzi S, Turricchia E. Similarity measures for OLAP sessions. Knowl Inf Syst. 2014;39(2):463–89.

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  4. Aufaure M-A, Beauger NK, Marcel P, Rizzi S, Vanrompay Y. Predicting your next OLAP query based on recent analytical sessions. In: Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery; 2013. p. 134–45.

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  5. Bellatreche L, Giacometti A, Marcel P, Mouloudi H, Laurent D. A personalization framework for OLAP queries. In: Proceedings of the ACM 8th International Workshop on Data Warehousing and OLAP; 2005. p. 9–18.

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  7. Giacometti A, Marcel P, Negre E. Recommending multidimensional queries. In: Proceedings of the 10th International Conference on Data Warehousing and Knowledge Discovery; 2009. p. 453–66.

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Author information

Authors and Affiliations

  1. Département Informatique, Laboratoire d’Informatique, Université François Rabelais Tours, Blois, France

    Patrick Marcel

Authors
  1. Patrick Marcel
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Corresponding author

Correspondence to Patrick Marcel .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Department of Computer Science, Aalborg University, Aalborg, Denmark

    Torben Bach Pedersen

  2. DISI, University of Bologna, Bologna, Italy

    Stefano Rizzi

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Marcel, P. (2018). OLAP Personalization and Recommendation. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_3191

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