RightNow eService Center: Internet Customer Service Using a Self-Learning Knowledge Base
Abstract
Delivering effective customer service via the Internet requires attention to many aspects of knowledge management if it is to be convenient and satisfying for customers, while at the same time efficient and economical for the company or other organization. In RightNow eService Center, such management is enabled by automatically gathering meta-knowledge about the Answer documents held in the core knowledge base. A variety of AI techniques are used to facilitate the construction, maintenance, and navigation of the knowledge base. These include collaborative filtering, swarm intelligence, fuzzy logic, natural language processing, text clustering, and classification rule learning. Customers using eService Center report dramatic decreases in support costs and increases in customer satisfaction due to the ease of use provided by the self-learning features of the knowledge base.
Cite
Text
Durbin et al. "RightNow eService Center: Internet Customer Service Using a Self-Learning Knowledge Base." AAAI Conference on Artificial Intelligence, 2002. doi:10.5555/777092.777217Markdown
[Durbin et al. "RightNow eService Center: Internet Customer Service Using a Self-Learning Knowledge Base." AAAI Conference on Artificial Intelligence, 2002.](https://mlanthology.org/aaai/2002/durbin2002aaai-rightnow/) doi:10.5555/777092.777217BibTeX
@inproceedings{durbin2002aaai-rightnow,
title = {{RightNow eService Center: Internet Customer Service Using a Self-Learning Knowledge Base}},
author = {Durbin, Stephen D. and Warner, Doug and Richter, J. Neal and Gedeon, Zuzana},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2002},
pages = {815-821},
doi = {10.5555/777092.777217},
url = {https://mlanthology.org/aaai/2002/durbin2002aaai-rightnow/}
}