GiveALink: mining a semantic network of bookmarks for web search and recommendation
Proceedings of the 3rd international workshop on Link discovery
User-induced links in collaborative tagging systems
Proceedings of the 18th ACM conference on Information and knowledge management
Blog interface producing mechanism in e-learning platform
ICACT'10 Proceedings of the 12th international conference on Advanced communication technology
Wisdom of artificial crowds algorithm for solving NP-hard problems
International Journal of Bio-Inspired Computation
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In this paper, we develop an information recommendation system based on information edited by various users. This system targets a social bookmark service. Our method for finding appropriate information is to gather each user's bookmark data on the Web and develop a system that analyzes the user's association. Assuming that users that have similar interests also have information associated to those interests, we describe user co-citation relationships as a network. We extract the sub-graph as the community in which each user centers from this network. And we develop a web service designed to automatically recommend new information regarding these interests. That service has a list of users who share similar preferences with the specified user and a system to present recommended information to the user.