User Modeling for Adaptive News Access

@misc{citeulike:691966, abstract = {We present a framework for adaptive news access, based on machine learning techniques specically designed for this task. First, we focus on the system's general functionality and system architecture.We then describe the interface and design of two deployed news agents that are part of the described architecture. While the rst agent provides personalized news through a web-based interface, the second system is geared towards wireless information devices such as PDAs (personal digital assistants) ...}, author = {Billsus, D. and Pazzani, M. }, citeulike-article-id = {691966}, keywords = {news, personalization, recommender, user-profile}, posted-at = {2006-06-10 21:58:20}, priority = {2}, title = {User Modeling for Adaptive News Access}, url = {http://citeseer.ist.psu.edu/billsus00user.html}, year = {2000} }

TY - GEN ID - citeulike:691966 L3 - citeulike-article-id:691966 N2 - We present a framework for adaptive news access, based on machine learning techniques specically designed for this task. First, we focus on the system's general functionality and system architecture.We then describe the interface and design of two deployed news agents that are part of the described architecture. While the rst agent provides personalized news through a web-based interface, the second system is geared towards wireless information devices such as PDAs (personal digital assistants) ... TI - User Modeling for Adaptive News Access KW - news KW - personalization KW - recommender KW - user-profile AU - Billsus, D AU - Pazzani, M PY - 2000/// UR - http://citeseer.ist.psu.edu/billsus00user.html ER -