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SMART: Semantic multidimensional group recommendations

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Abstract

The rising availability of data in the information systems has boosted the challenging problem of queries recommendation, especially in OLAP systems. In this paper, we introduce an innovative 𝓢ℳ𝓐𝓡𝓣 system for semantic multidimensional group recommendations to enhance the querying formulation process. Indeed, we describe the problem of group recommendation and define its semantics through introducing our group profiling ontology. Thus, we infer the analysts’ ongoing behaviors on our ontological concepts using a weighted summation strategy. Based on our ontological representation, we propose a new method for deriving relevant semantic recommendations (i.e., complete and queries fragments). In addition, an optimization technique for selecting the most interesting visualization of recommendations is proposed. Carried out experiments of our 𝓢ℳ𝓐𝓡𝓣 system on real built financial data warehouse highlight encouraging results in terms of precision and recall.

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Notes

  1. The data warehouse is built using the available information at http://www.bvmt.com.tn/publications/?view=cours http://www.bvmt.com.tn/publications/?view=cours.

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Authors and Affiliations

  1. High Institute of Management of Tunis, University of Tunis, Tunis, Tunisia

    Eya Ben Ahmed, Wafa Tebourski & Wahiba Ben Abdessalem Karaa

  2. High Institute of Computer and Multimedia of Sfax, University of Sfax, Tunis, Tunisia

    Faïez Gargouri

Authors
  1. Eya Ben Ahmed
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  2. Wafa Tebourski
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  3. Wahiba Ben Abdessalem Karaa
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  4. Faïez Gargouri
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Correspondence to Eya Ben Ahmed.

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Ben Ahmed, E., Tebourski, W., Ben Abdessalem Karaa, W. et al. SMART: Semantic multidimensional group recommendations. Multimed Tools Appl 74, 10419–10437 (2015). https://doi.org/10.1007/s11042-014-2174-0

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  • DOI: https://doi.org/10.1007/s11042-014-2174-0

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