A Learning System for Selective Dissemination of Information
Abstract
New methods and new systems are needed to filter or to selectively distribute the increasing volume of electronic information being produced nowadays. An effective information filtering system is one that provides the exact information that fulfills a user's interest with the minimum effort by the user to describe it. Such a system will have to be adaptive to the user changing interest. In this paper we present a learning system for information filtering and selective information dissemination. The learning algorithm is described and the effectiveness of the system is evaluated in a true information filtering style. 1 Introduction Information overload is an increasing problem in many domains. New information services (e.g. news services, electronic mail, libraries and databanks) deliver to the user an increasing volume of digital information. Often the information delivered to the user does not match the user interest and it ends up overloading the user, who will have to manually sele...
Cite
Text
Amati et al. "A Learning System for Selective Dissemination of Information." International Joint Conference on Artificial Intelligence, 1997.Markdown
[Amati et al. "A Learning System for Selective Dissemination of Information." International Joint Conference on Artificial Intelligence, 1997.](https://mlanthology.org/ijcai/1997/amati1997ijcai-learning/)BibTeX
@inproceedings{amati1997ijcai-learning,
title = {{A Learning System for Selective Dissemination of Information}},
author = {Amati, Gianni and Crestani, Fabio and Ubaldini, Flavio},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1997},
pages = {764-769},
url = {https://mlanthology.org/ijcai/1997/amati1997ijcai-learning/}
}