| Summary: | 碩士 === 國立交通大學 === 資訊管理研究所 === 100 === The development of Internet is thriving in recent years. People don't confined learn the new knowledge to books. After search engines appear, people can easily learn and search the new knowledge. Unfortunately amount of data is getting huge in the internet, many search engines do not explicitly support collaboration during search and this let people can not collaborate to filter data.
This paper introduces two systems that social bookmarking website based on cloud computing and IE Toolbar. These systems support users by harnessing the bookmark's metadata、users' similarity calculation、PageRank and Reputation Model as the base for websites and users recommendation. Therefore, a key contribution of this paper is to develop a collaboration system and to design IE Toolbar to work with mainstream search engines. Let user can easily make friend with another user, collaborate to filter data and share their knowledge.
Finally, the experiment invites 52 users and they use this system about one week. The research findings show that reputation, PageRank and citation times are positive relationship. Personality and interactivity can enrich the content and enlarge the user interesting in this system.
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