Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality
Abstract
Increasing dialogue efficiency in case-based reasoning (CBR) must be balanced against the risk of commitment to a sub-optimal solution. Focusing on incremental query elicitation in recommender systems, we examine the limitations of naive strategies such as terminating the dialogue when the similarity of any case reaches a predefined threshold. We also identify necessary and sufficient conditions for recommendation dialogues to be terminated without loss of solution quality. Finally, we evaluate a number of attribute-selection strategies in terms of dialogue efficiency given the requirement that there must be no loss of solution quality. 1
Cite
Text
McSherry. "Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality." International Joint Conference on Artificial Intelligence, 2003.Markdown
[McSherry. "Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality." International Joint Conference on Artificial Intelligence, 2003.](https://mlanthology.org/ijcai/2003/mcsherry2003ijcai-increasing/)BibTeX
@inproceedings{mcsherry2003ijcai-increasing,
title = {{Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality}},
author = {McSherry, David},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2003},
pages = {121-126},
url = {https://mlanthology.org/ijcai/2003/mcsherry2003ijcai-increasing/}
}