Skip to Main content Skip to Navigation
New interface
Conference papers

Banner Personalization for e-Commerce

Abstract : Real-time website personalization is a concept that is being discussed for more than a decade, but has only recently been applied in practice, according to new marketing trends. These trends emphasize on delivering user-specific content based on behavior and preferences. In this context, banner recommendation in the form of personalized ads is an approach that has attracted a lot of attention. Nevertheless, banner recommendation in terms of e-commerce main page sliders and static banners is even today an underestimated problem, as traditionally only large e-commerce stores deal with it. In this paper we propose an integrated framework for banner personalization in e-commerce that can be applied in small-medium e-retailers. Our approach combines topic-models and a neural network, in order to recommend and optimally rank available banners of an e-commerce store to each user separately. We evaluated our framework against a dataset from an active e-commerce store and show that it outperforms other popular approaches.
Document type :
Conference papers
Complete list of metadata

Cited literature [25 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Thursday, October 24, 2019 - 12:50:31 PM
Last modification on : Thursday, October 24, 2019 - 12:54:43 PM
Long-term archiving on: : Saturday, January 25, 2020 - 3:45:05 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Ioannis Maniadis, Konstantinos N. Vavliakis, Andreas L. Symeonidis. Banner Personalization for e-Commerce. 15th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2019, Hersonissos, Greece. pp.635-646, ⟨10.1007/978-3-030-19823-7_53⟩. ⟨hal-02331309⟩



Record views


Files downloads