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A First Framework for Top-K Cubes Queries

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Book cover Advances in Conceptual Modeling (ER 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9382))

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Abstract

Data Warehouse (DW) and OLAP systems are effective solutions for the online analysis of large volumes of data structured as cubes. Usually organizations and enterprises require several cubes for their activities. In this context, we define a new kind of queries: “Top-k Cubes queries”. Top-K cubes queries allow searching the most relevant k-cubes among a collection of cubes. Then, in this paper we propose a first framework for Top-K cubes queries where queries are expressed in natural language to meet the easiness need of unskilled IT decision-makers. An implementation in a ROLAP architecture is also provided.

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References

  1. Kuchmann-Beauger, N., Aufaure, M.-A.: A natural language interface for data warehouse question answering. In: Muñoz, R., Montoyo, A., Métais, E. (eds.) NLDB 2011. LNCS, vol. 6716, pp. 201–208. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  2. Giacometti, A., Marcel, P., Negre, E.: A framework for recommending OLAP queries. In: 11th International Workshop on Data Warehousing and OLAP, DOLAP 2008, pp. 73–80. Proceedings of the ACM, New York (2008)

    Google Scholar 

  3. Golfarelli, M., Rizzi, S., Biondi, P.: myOLAP: An approach to express and evaluate OLAP preferences. IEEE Trans. Knowl. Data Eng. 23(7), 1050–1064 (2011)

    Article  Google Scholar 

  4. Jerbi, H., Ravat, F., Teste, O., Zurfluh, G.: Preference-based recommendations for OLAP analysis. In: Pedersen, T.B., Mohania, M.K., Tjoa, A.M. (eds.) DaWaK 2009. LNCS, vol. 5691, pp. 467–478. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  5. Kozmina, N.: Adding recommendations to OLAP reporting tool. In: 5th International Conference on Enterprise Information Systems, vol. 1, pp. 169–176. ICEIS, France (2013)

    Google Scholar 

  6. Khemiri, R., Bentayeb, F.: FIMIOQR: Frequent itemsets mining for interactive OLAP query recommendation. In: The Fifth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA), pp. 9–14. DBKDA, Seville, Spain (2013)

    Google Scholar 

  7. Xin, D., Han, J., Cheng, H., Li, X.: Answering Top-k queries with multi-dimensional selections: The ranking cube approach. In: 32nd International Conference on Very Large Data Bases, pp. 463–474. Korea (2006)

    Google Scholar 

  8. Luo, Z.W., Ling, T.-W., Ang, C.-H., Lee, S.-Y., Cui, B.: Range top/bottom k queries in OLAP sparse data cubes. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, p. 678. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  9. Loh, Z.X., Ling, T.-W., Ang, C.-H., Lee, S.-Y.: Adaptive method for range top-k queries in OLAP data cubes. In: Hameurlain, A., Cicchetti, R., Traunmüller, R. (eds.) DEXA 2002. LNCS, vol. 2453, p. 648. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  10. Ding, B., Zhao, B., Lin, C.X., Han, J., Zhai, C.: Topcells: keyword-based search of Top-k aggregated documents in text cube. In: IEEE International Conference Data Eng. (ICDE), pp. 381–384 (2010)

    Google Scholar 

  11. Sagayaraj Francis, F., Xavier, P.P.: An effective method to answer OLAP queries using R*-Trees in distributed environment. Int. J. Comput. Appl. IJCA 107 (2014)

    Google Scholar 

  12. Bimonte, S., Pradel, M., Boffety, D., Tailleur, A., André, G., Bzikha, R., Chanet, J.-P.: A New sensor-based spatial OLAP architecture centered on an agricultural farm energy-use diagnosis tool. IJDSST 5(4), 1–20 (2013)

    Google Scholar 

  13. Abelló, A., Darmont, J., Etcheverry, L., Golfarelli, M., Mazón López, J.N., Naumann, F., Vossen, G.: Fusion cubes: towards self-service business intelligence. Int. J. Data Warehousing Min. IJDWM 9(2), 66–88. USA (2013)

    Google Scholar 

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Correspondence to Rahma Djiroun .

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Djiroun, R., Bimonte, S., Boukhalfa, K. (2015). A First Framework for Top-K Cubes Queries. In: Jeusfeld, M., Karlapalem, K. (eds) Advances in Conceptual Modeling. ER 2015. Lecture Notes in Computer Science(), vol 9382. Springer, Cham. https://doi.org/10.1007/978-3-319-25747-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-25747-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25746-4

  • Online ISBN: 978-3-319-25747-1

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