C. Chen, M. Chen, and Y. Sun. Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, page 257--262. New York, NY, USA, ACM, (2001)
DOI: 10.1145/502512.502548
Abstract
In this paper, we present PVA, an adaptive personal view information agent system to track, learn and manage, user's interests in Internet documents. When user's interests change, PVA, in not only the contents, but also in the structure of user profile, is modified to adapt to the changes. Experimental results show that modulating the structure of user profile does increase the accuracy of personalization systems.
%0 Conference Paper
%1 citeulike:2237030
%A Chen, Chien C.
%A Chen, Meng C.
%A Sun, Yeali
%B Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
%C New York, NY, USA
%D 2001
%I ACM
%K personalization user-profile www
%P 257--262
%R 10.1145/502512.502548
%T PVA: a self-adaptive personal view agent system
%U http://dx.doi.org/10.1145/502512.502548
%X In this paper, we present PVA, an adaptive personal view information agent system to track, learn and manage, user's interests in Internet documents. When user's interests change, PVA, in not only the contents, but also in the structure of user profile, is modified to adapt to the changes. Experimental results show that modulating the structure of user profile does increase the accuracy of personalization systems.
%@ 1-58113-391-X
@inproceedings{citeulike:2237030,
abstract = {{In this paper, we present PVA, an adaptive personal view information agent system to track, learn and manage, user's interests in Internet documents. When user's interests change, PVA, in not only the contents, but also in the structure of user profile, is modified to adapt to the changes. Experimental results show that modulating the structure of user profile does increase the accuracy of personalization systems.}},
added-at = {2018-03-19T12:24:51.000+0100},
address = {New York, NY, USA},
author = {Chen, Chien C. and Chen, Meng C. and Sun, Yeali},
biburl = {https://www.bibsonomy.org/bibtex/2d3ce2524e8ad43302e63e87fa3961235/aho},
booktitle = {Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining},
citeulike-article-id = {2237030},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=502548},
citeulike-linkout-1 = {http://dx.doi.org/10.1145/502512.502548},
doi = {10.1145/502512.502548},
interhash = {78eb61b48a6ad107172fc73cefa2e943},
intrahash = {d3ce2524e8ad43302e63e87fa3961235},
isbn = {1-58113-391-X},
keywords = {personalization user-profile www},
location = {San Francisco, California},
pages = {257--262},
posted-at = {2008-01-16 02:20:31},
priority = {2},
publisher = {ACM},
series = {KDD '01},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{PVA: a self-adaptive personal view agent system}},
url = {http://dx.doi.org/10.1145/502512.502548},
year = 2001
}