A Hybrid User Model for News Story Classification

@misc{citeulike:691964, abstract = {. We present an intelligent agent designed to compile a daily news program for individual users. Based on feedback from the user, the system automatically adapts to the user's preferences and interests. In this paper we focus on the system's user modeling component. First, we motivate the use of a multi-strategy machine learning approach that allows for the induction of user models that consist of separate models for long-term and short-term interests. Second, we investigate the utility of...}, author = {Billsus, D. and Pazzani, M. }, citeulike-article-id = {691964}, posted-at = {2007-05-11 18:07:13}, priority = {2}, title = {A Hybrid User Model for News Story Classification}, url = {http://citeseer.ist.psu.edu/billsus99hybrid.html}, year = {1999} }

TY - GEN ID - citeulike:691964 L3 - citeulike-article-id:691964 TI - A Hybrid User Model for News Story Classification N2 - . We present an intelligent agent designed to compile a daily news program for individual users. Based on feedback from the user, the system automatically adapts to the user's preferences and interests. In this paper we focus on the system's user modeling component. First, we motivate the use of a multi-strategy machine learning approach that allows for the induction of user models that consist of separate models for long-term and short-term interests. Second, we investigate the utility of... AU - Billsus, D AU - Pazzani, M PY - 1999/// UR - http://citeseer.ist.psu.edu/billsus99hybrid.html ER -