Evaluating Preference-Based Search Tools: A Tale of Two Approaches

Abstract

People frequently use the world-wide web to find their most preferred item among a large range of options. We call this task preference-based search. The most common tool for preference-based search on the WWW today obtains users' preferences by asking them to fill in a form. It then returns a list of items that most closely match these preferences. Recently, several researchers have proposed tools for preference-based search that elicit preferences from the critiques a user actively makes on examples shown to them. We carried out a user study in order to compare the performance of traditional preference-based search tools using form-filling with two different versions of an example-critiquing tool. The results show that example critiquing achieves almost three times the decision accuracy, while requiring only slightly higher interaction effort.

Cite

Text

Viappiani et al. "Evaluating Preference-Based Search Tools: A Tale of Two Approaches." AAAI Conference on Artificial Intelligence, 2006.

Markdown

[Viappiani et al. "Evaluating Preference-Based Search Tools: A Tale of Two Approaches." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/viappiani2006aaai-evaluating/)

BibTeX

@inproceedings{viappiani2006aaai-evaluating,
  title     = {{Evaluating Preference-Based Search Tools: A Tale of Two Approaches}},
  author    = {Viappiani, Paolo and Faltings, Boi and Pu, Pearl},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2006},
  pages     = {205-212},
  url       = {https://mlanthology.org/aaai/2006/viappiani2006aaai-evaluating/}
}