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) ...
%0 Generic
%1 citeulike:691966
%A Billsus, D.
%A Pazzani, M.
%D 2000
%K news personalization recommender user-profile
%T User Modeling for Adaptive News Access
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.4426
%X 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) ...
@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) ...}},
added-at = {2018-03-19T12:24:51.000+0100},
author = {Billsus, D. and Pazzani, M.},
biburl = {https://www.bibsonomy.org/bibtex/2d5bcedb7b1c75f627b02d97266071f18/aho},
citeulike-article-id = {691966},
citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.4426},
interhash = {176f415b93c367b2816c0467e377d753},
intrahash = {d5bcedb7b1c75f627b02d97266071f18},
keywords = {news personalization recommender user-profile},
posted-at = {2006-06-10 21:58:20},
priority = {2},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{User Modeling for Adaptive News Access}},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.4426},
year = 2000
}