Detecting Uninteresting Content in Text Streams
Omar Alonso, Chad Carson, David Gerster, Xiang Ji · 2010
A BST R A C T We study the problem of identifying uninteresting content in text streams from micro-blogging services such as Twitter. Our premise is that truly mundane content is not interesting in any context, and thus can be quickly filtered using simple queryindependent features. Such a filter could be used for tiering indexes in a micro-blog search engine, with the filtered uninteresting content relegated to the less frequently accessed tiers.