TY  - CHAP
AB  - Configuring complex products can be a challenge due to the huge number of configuration possibilities. In this paper, our goal is to foster the development of intelligent configuration assistants that can support customers in configuring
complex products. We formalize the task as a machine learning problem and in particular as a learning-to-rank problem. Given pairwise preferences elicited from experts, we show that we can train a model using support vector machines that ranks possible products according to their relevance to a given set of requirements specified by a user.
DO  - 10.1007/978-3-319-56994-9_59
KW  - Product Configuration
KW  - Ranking
KW  - Information Retrieval
KW  - Machine Learning
LA  - eng
PY  - 2018
SP  - 866-879
T3  - Proceedings of the SAI Intelligent Systems Conference (IntelliSys) 2016. Vol. 1
TI  - Providing Intelligent Assistance for Product Configuration in Manufacturing. A Learning-to-Rank Approach
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-29017949
Y2  - 2024-11-25T06:06:43
ER  -