Recommending content from social information streams
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People increasingly keep up with the "newest news" through information streams (such as Twitter). ...
People increasingly keep up with the "newest news" through information streams (such as Twitter).
To alleviate information overload and better direct user attention, we explored dimensions for designing a recommender system that selects promising subsets of content for consideration, models user topic interest, and leverages social interaction processes.
The best performing algorithm -- implemented as a prototype web-based tool -- improved the percentage of interesting content to 72% (from a baseline of 33%). The competencies and results of this work can be generalized to other enterprise and consumer information streams.
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