Abstract
The amount of information on web increases explosively, so it is difficult for web users to find web pages they want. There are some approaches to resolve this problem, such as semantic web which make web information systematic, the improvement of search engines’ algorithm, and so on. Dealing with web as a huge database, these technologies works well, however, they cannot provide any useful solutions to get hot news which expands quickly to the world because of their time lag.
In this paper, we propose a system whose users can know currently and heavily viewed web pages. The key features of this system are as follows: (1) to find hot news in web, (2) to provide recommendations to users without any content analysis, and (3) to apply the system to other communication tools like IM as their infrastructure to find appropriate contact targets. We describe our policy of the system implementation and show the result of a pilot experiment with a pilot implementation.
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© 2007 Springer-Verlag Berlin Heidelberg
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Maruyama, K., Takasuka, K., Yagihara, Y., Machida, S., Shirai, Y., Terada, M. (2007). Real-Time Discovery of Currently and Heavily Viewed Web Pages. In: Filipe, J., Cordeiro, J., Pedrosa, V. (eds) Web Information Systems and Technologies. Lecture Notes in Business Information Processing, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74063-6_20
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DOI: https://doi.org/10.1007/978-3-540-74063-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74062-9
Online ISBN: 978-3-540-74063-6
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