UNDR: User-Needs-Driven Ranking of Products in E-Commerce

no code implementations • 13 Feb 2023 • Andrea Papenmeier, Daniel Hienert, Firas Sabbah, Norbert Fuhr, Dagmar Kern

As a user-centered approach that does not rely on post-purchase ratings or reviews, our method bypasses the cold-start problem while still reflecting the needs of an average customer.

Dataset of Natural Language Queries for E-Commerce

no code implementations • 13 Feb 2023 • Andrea Papenmeier, Dagmar Kern, Daniel Hienert, Alfred Sliwa, Ahmet Aker, Norbert Fuhr

Shopping online is more and more frequent in our everyday life.

Conversational Search Information Retrieval +2

Starting Conversations with Search Engines -- Interfaces that Elicit Natural Language Queries

no code implementations • 13 Feb 2023 • Andrea Papenmeier, Dagmar Kern, Daniel Hienert, Alfred Sliwa, Ahmet Aker, Norbert Fuhr

Search systems on the Web rely on user input to generate relevant results.

Chatbot Information Retrieval +2

How model accuracy and explanation fidelity influence user trust

no code implementations • 26 Jul 2019 • Andrea Papenmeier, Gwenn Englebienne, Christin Seifert

We also found that users cannot be tricked by high-fidelity explanations into having trust for a bad classifier.

BIG-bench Machine Learning Fairness +1