Coverage-Optimized Retrieval
Abstract
We present a generalization of similarity-based retrieval in recommender systems which ensures that for any case that is acceptable to the user, the retrieval set contains a case that is at least as good in an objective sense and so also likely to be acceptable. Our approach recognizes that similarity to the target query is only one of several possible criteria according to which a given case might be considered at least as good as another.
Cite
Text
McSherry. "Coverage-Optimized Retrieval." International Joint Conference on Artificial Intelligence, 2003.Markdown
[McSherry. "Coverage-Optimized Retrieval." International Joint Conference on Artificial Intelligence, 2003.](https://mlanthology.org/ijcai/2003/mcsherry2003ijcai-coverage/)BibTeX
@inproceedings{mcsherry2003ijcai-coverage,
title = {{Coverage-Optimized Retrieval}},
author = {McSherry, David},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2003},
pages = {1349-1350},
url = {https://mlanthology.org/ijcai/2003/mcsherry2003ijcai-coverage/}
}