GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
Open user profiles for adaptive news systems: help or harm?
Proceedings of the 16th international conference on World Wide Web
The adaptive web
InterSynd: a web syndication intermediary that makes recommendations
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Web user browse behavior characteristic analysis based on a BC tree
AMT'10 Proceedings of the 6th international conference on Active media technology
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As the Internet has been commonly used in our everyday lives, we have been able to obtain large amount of information from it, whereas we have simultaneously had a problem that it is difficult to find proper information for us from the large amount of information on the Web. Although many information recommendation methods have been proposed in order to solve this problem, most recommendation methods are based on a large amount of user's personal data such as operation log, schedule, etc - which means that we have to manage a large amount of personal data in the system in order to provide proper information to users, and it would be expensive to construct such a system. With this background, in this study, against aiming to construct a sophisticated information recommendation system based on large personal data, we propose a handy and not expensive information recommendation method, working beside a normal search engine, which does not depend on user profile data, but on topical news information.