Discovering trending phrases on information streams

Krishna Y. Kamath, James Caverlee
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
We study the problem of efficient discovery of trending phrases from high-volume text streams -be they sequences of Twitter messages, email messages, news articles, or other timestamped text documents. Most exisiting approaches return top-k trending phrases. But, this approach neither guarantees that the top-k phrases returned are all trending, nor that all trending phrases are returned. In addition, the value of k is difficult to set and is indifferent to stream dynamics. Hence, we propose an
more » ... pproach that identifies all the trending phrases in a stream and is flexible to the changing stream properties.
doi:10.1145/2063576.2063937 dblp:conf/cikm/KamathC11 fatcat:opaazarlrje3rbqjuxhr2dsj3e