QeNoBi : a system for QuErying and miNing BehavIoral patterns [demonstration paper] - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2021

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

A. Chibah
  • Fonction : Auteur
S. Amer-Yahi
  • Fonction : Auteur

Résumé

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
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Dates et versions

hal-03278948 , version 1 (06-07-2021)

Identifiants

Citer

A. Chibah, S. Amer-Yahi, Laure Berti-Équille. QeNoBi : a system for QuErying and miNing BehavIoral patterns [demonstration paper]. International Conference on Data Engineering (ICDE), IEEE, pp.2673-2676, 2021, 978-1-7281-9185-0. ⟨hal-03278948⟩
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