Authors:
Kazutaka Maruyama
1
;
Kiyotaka Takasuk
2
;
Yuta Yagihara
2
;
Satoshi Machida
2
;
Yuichiro Shirai
2
and
Minoru Terada
2
Affiliations:
1
Information Processing Center, The University of Electro-Communications, Japan
;
2
The University of Electro-Communications, Japan
Keyword(s):
Peer-to-peer, clustering, web browsing, browser extension.
Related
Ontology
Subjects/Areas/Topics:
Data Engineering
;
Ontologies and the Semantic Web
;
Personalized Web Sites and Services
;
Searching and Browsing
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Personalization
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.