Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 121-125.
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.
@inproceedings{ijcai2003p17,
title = {Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality},
author = {McSherry, David},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {121--125},
year = {2003},
url = {https://ijcai.org/proceedings/2003/17},
}
TY - CPAPER TI - Increasing Dialogue Efficiency in Case-Based Reasoning Without Loss of Solution Quality AU - McSherry, David T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 121 EP - 125 UR - https://ijcai.org/proceedings/2003/17 ER -Copied
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