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/}
}