Chibah A., Amer-Yahi S., Berti-Equille Laure. (2021). QeNoBi : a system for QuErying and miNing BehavIoral patterns [demonstration paper]. In :
International Conference on Data Engineering (ICDE). Chania : IEEE, 2673-2676. ICDE.International Conference on Data Engineering, 37., Chania (GRC), 2021/04/19-22. ISBN 978-1-7281-9185-0.
Titre du document
QeNoBi : a system for QuErying and miNing BehavIoral patterns [demonstration paper]
International Conference on Data Engineering (ICDE)
Source
Chania : IEEE, 2021,
2673-2676 ISBN 978-1-7281-9185-0
Colloque
ICDE.International Conference on Data Engineering, 37., Chania (GRC), 2021/04/19-22
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
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
;
Economie : secteurs d'activité [096]
;
Informatique [122]
