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QeNoBi : a system for QuErying and miNing BehavIoral patterns [demonstration paper]

Author

Listed:
  • A. Chibah
  • S. Amer-Yahi
  • Laure Berti-Équille

    (UMR 228 Espace-Dev, Espace pour le développement - IRD - Institut de Recherche pour le Développement - UPVD - Université de Perpignan Via Domitia - AU - Avignon Université - UR - Université de La Réunion - UM - Université de Montpellier - UG - Université de Guyane - UA - Université des Antilles)

Abstract

We demonstrate QeNoBi, a system for mining and querying customer behavioral patterns. QeNoBi combines an interactive visual interface, on-demand mining, and efficient topk processing, to provide the exploration of customer behavior over time. QeNoBi relies on two distinct data models: a customercentric graph that represents customers with similar purchasing behaviors and is annotated with a change algebra to reflect their behavior evolution, and product-centric time series that reflect the evolution of customer purchases over time. Users can query both representations along three dimensions : shape (the sketched trend of the behavior), scope (the set of customers/products of interest), and time granularity. QeNoBi provides a holistic behavior exploration capability by allowing users to seamlessly switch between customer-centric and product-centric views in a coordinated manner, thereby catering to various needs. A demonstration of QeNoBi is available at https://bit.ly/2HlcO3S

Suggested Citation

  • A. Chibah & S. Amer-Yahi & Laure Berti-Équille, 2021. "QeNoBi : a system for QuErying and miNing BehavIoral patterns [demonstration paper]," Post-Print hal-03278948, HAL.
    • Handle: RePEc:hal:journl:hal-03278948
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