Giving temporal order to news corpus
H. Uejima, T. Miura, Isamu Shioya · 2005
We propose a new mechanism to give temporal order to a news article in a form of times-tamps. Here we learn temporal data in advance to extract ordering by means of incremental clustering and then we estimate most likely order to news text. In this work, we examine TDT2 corpus and we show how well our approach works by some experiments.