Timeline Generation After Summarization of Evolutionary Tweet Streams

Abstract: In a world of rapidly evolving communication systems managing intelligible and required data is a tough ask. Short-t messages in text form such as tweets are being created and shared at an unprecedented rate. Tweets, in their raw form while being informative, can also be enormous. It’s a nightmare for both end-users and data analysts to plow through millions of tweets which contain huge amount of noise and redundancy. In this paper, an innovative continuous summarization framework called Sumblr to reduce the problem. Sumblr is way different than the traditional summarization methods which focuses on static and small scale data set, rather it is designed to deal with large scale, dynamic and fast arriving tweet streams. Keywords: Continuous Summarization, Timeline, Tweet Stream, Summary