A Predictive Approach to Help-Desk Response Generation
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1665-1669.
Abstract
We are developing a corpus-based approach for the prediction of help-desk responses from features in customers' emails, where responses are represented at two levels of granularity: document and sentence. We present an automatic and human-based evaluation of our system's responses. The automatic evaluation involves textual comparisons between generated responses and responses composed by help-desk operators. Our results show that both levels of granularity produce good responses, addressing inquiries of different kinds. The human-based evaluation measures response informativeness, and confirms our conclusion that both levels of granularity produce useful responses.
@inproceedings{ijcai2007p269,
title = {A Predictive Approach to Help-Desk Response Generation},
author = {Marom, Yuval and Zukerman, Ingrid},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1665--1669},
year = {2007},
url = {https://ijcai.org/proceedings/2007/269},
}
TY - CPAPER TI - A Predictive Approach to Help-Desk Response Generation AU - Marom, Yuval AU - Zukerman, Ingrid T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1665 EP - 1669 UR - https://ijcai.org/proceedings/2007/269 ER -Copied
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