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Transparent Personalization in E-Commerce


Contact: Michael Färber, Anna Nguyen




Project Status: active


Description

In the project "TransPer: Transparent Personalization in E-Commerce" aspects of causality, robustness and uncertainty of AI applications in an industrial environment are considered. The project specifically focuses on how product recommendations in the e-commerce sector can be made more transparent in order to achieve better customer satisfaction and to ensure compliance with legal requirements. In the project, the KIT Institute AIFB under the direction of Dr. Färber develops modules to make product recommendations in online web shops transparent. Econda GmbH, which works with around 20% of all German online shops, acts as an industrial partner.


Involved Persons
Philipp Sorg, Michael Färber, Anna Nguyen


Information

n.a.
Funding: BMBF


Partners

Econda GmbH


Research Group

Web Science


Area of Research

Deep Learning, Artificial Intelligence


Publications Belonging to the Project
article
 - book
 - incollection
 - booklet
 - proceedings
 - phdthesis
 - techreport
 - deliverable
 - manual
 - misc
 - unpublished





inproceedings
Anna Nguyen, Franz Krause, Daniel Hagenmayer, Michael Färber
Quantifying Explanations of Neural Networks in E-Commerce Based on LRP
Proceedings of Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'21), Springer, Juli, 2021
(Details)


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