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Subscribers to the popular news or blog feeds (RSS/Atom) often face the problem of information overload as these feed sources usually deliver large number of items periodically. One solution to this problem could be clustering similar items in the feed reader to make the information more manageable for a user. Clustering items at the feed reader end is a challenging task as usually only a small part of the actual paper is received through the feed. This paper proposes a method of improving the accuracy of clustering short texts by enriching their representation with additional features from Wikipedia.
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