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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