The increasing amount of information on the internet makes it hard to filter out relevant parts. Every second hundreds of news-articles and blog-entries are written. A subscriber to this constant stream of information quickly looses overview - a typical needle-in-a-haystack problem. Especially in the field of news-reading, software can help to increase efficiency by personalized filtering mechanisms. This filtering can be predictive based on previous user-choices, but also heeds the power of social networks: Users help each other by marking relevant information. The author Ingo Schommer investigates the conceptual and practical development of a web-based news-reader with advanced filtering features. Research is conducted in the field of information visualization and filtering as well as in competitive products and their shortcomings. The solution will mainly target pro-users who are already accustomed with news-reading, the modern "information junkies."
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