| Abstract |
|
In this investigation, we propose a new mechanism to give temporal order to a news article in a form of timestamps. 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 vorpus and we show how well our approach works by some experiments.
|
 Additional Information
|
Index Terms- TDT, stream data, incremental clustering, timestamp estimation
Citation:
Hiroshi Uejima, Takao Miura, Isamu Shioya,
"Giving Temporal Order to News Corpus,"
ictai,
pp. 208-215,
16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'04),
2004
|
