Research on Modeling User’s Preference in the Steel E-Trading Platform
2015 ◽
Vol 743
◽
pp. 687-691
Keyword(s):
In order to meet the increasing personalized needs of users in the steel trading platform, the intelligent recommendation system has been introduced into the platform. And the users’ interests and preferences-based modeling is the key and foundation of recommendation system, and changes with the change of time. So, in this paper, the user preferences are divided into long-term and short-term firstly, then the users’ basic information vectors and cluster method are used to model users’ long-term interests and preferences, while mining and analyzing users’ operating records in the platform to model users’ the short-term. Finally, the whole interest and preference’s model of user will be built by integrating the two models.
2020 ◽
Vol 34
(01)
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pp. 214-221
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2017 ◽
Vol 26
(02)
◽
pp. 1760012
◽
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1990 ◽
Vol 48
(3)
◽
pp. 374-375
1995 ◽
Vol 28
(1)
◽
pp. 121-140
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