# Recommender Systems for Configuration Knowledge Engineering

arXiv: https://arxiv.org/abs/2102.08113 · HTML: https://mlsanity.com/paper/2102.08113/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 22 references that are in the map.
- First posted on arXiv 16 Feb 2021.

## Built on by (most cited first, 1 of 1)

- [An Overview of Direct Diagnosis and Repair Techniques in the WeeVis Recommendation Environment](https://mlsanity.com/paper/2102.12327/) (2021)

## Abstract (arXiv)

The knowledge engineering bottleneck is still a major challenge in configurator projects. In this paper we show how recommender systems can support knowledge base development and maintenance processes. We discuss a couple of scenarios for the application of recommender systems in knowledge engineering and report the results of empirical studies which show the importance of user-centered configuration knowledge organization.