A topic detection and tracking system with TF-density

In the past, news consumption took place predominantly via newspapers and were hard to track. Nowadays, the rapid growth of the Internet means that news are continually being shared and stored on a previously unimaginable scale. It is now possible to access several news stories on the same topic on a single web page. In this paper, we proposed a topic detection and tracking system with a new word measurement scheme named TF-Density. TF-Density is a new algorithm modified from the well-known TF-IWF and TF-IDF algorithms to provide a more precise and efficient method to recognize the important words in the text. Through our experiments, we demonstrated that our proposed topic detection and tracking system is capable of providing more precise and convenient result for the tracking of news by users.