PROJECT TITLE :

Context Adaptation for Smart Recommender Systems

ABSTRACT:

Contextual factors are considered an necessary mediator for improving recommender system performance. Within the e-commerce sector, such contextual factors as users' real-time approach and budget play a critical role in shoppers' call-creating processes. Using a context-aware approach, the authors' recommendation model can identify users' state of mind and budget based mostly on clickstream knowledge. They've deployed their model on a French e-commerce web site for a comparative A/B take a look at. Results show that usage of the context-aware system is considerably on top of that for the benchmarking system.


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