Extracting Chatbot Knowledge from Online Discussion Forums
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 423-427.
Abstract
This paper presents a novel approach for extracting high-quality <thread-title, reply> pairs as chat knowledge from online discussion forums so as to efficiently support the construction of a chatbot for a certain domain. Given a forum, the high-quality <thread-title, reply> pairs are extracted using a cascaded framework. First, the replies logically relevant to the thread title of the root message are extracted with an SVM classifier from all the replies, based on correlations such as structure and content. Then, the extracted <thread-title, reply> pairs are ranked with a ranking SVM based on their content qualities. Finally, the Top-N <thread-title, reply> pairs are selected as chatbot knowledge. Results from experiments conducted within a movie forum show the proposed approach is effective.
@inproceedings{ijcai2007p66,
title = {Extracting Chatbot Knowledge from Online Discussion Forums},
author = {Huang, Jizhou and Zhou, Ming and Yang, Dan},
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 = {423--427},
year = {2007},
url = {https://ijcai.org/proceedings/2007/66},
}
TY - CPAPER TI - Extracting Chatbot Knowledge from Online Discussion Forums AU - Huang, Jizhou AU - Zhou, Ming AU - Yang, Dan T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 423 EP - 427 UR - https://ijcai.org/proceedings/2007/66 ER -Copied
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