Empirical Inference Conference Paper 2005

A Machine Learning Approach to Conjoint Analysis

Choice-based conjoint analysis builds models of consumers preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learning community to solve more efficiently this problem. Thus, we propose two algorithms to estimate quickly and accurately consumer preferences.

Author(s): Chapelle, O. and Harchaoui, Z.
Book Title: Advances in Neural Information Processing Systems 17
Journal: Advances in Neural Information Processing Systems
Pages: 257-264
Year: 2005
Month: July
Day: 0
Editors: Saul, L.K. , Y. Weiss, L. Bottou
Publisher: MIT Press
Bibtex Type: Conference Paper (inproceedings)
Address: Cambridge, MA, USA
Event Name: Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004)
Event Place: Vancouver, BC, Canada
Digital: 0
Electronic Archiving: grant_archive
ISBN: 0-262-19534-8
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex

@inproceedings{2777,
  title = {A Machine Learning Approach to Conjoint Analysis},
  journal = {Advances in Neural Information Processing Systems},
  booktitle = {Advances in Neural Information Processing Systems 17},
  abstract = {Choice-based conjoint analysis builds models of consumers preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learning community to solve more efficiently this problem. Thus, we propose two algorithms to estimate quickly and accurately consumer preferences.},
  pages = {257-264},
  editors = {Saul, L.K. , Y. Weiss, L. Bottou},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = jul,
  year = {2005},
  slug = {2777},
  author = {Chapelle, O. and Harchaoui, Z.},
  month_numeric = {7}
}