New Event Detection Based on Division Comparison of Subtopic
Fan Ji · Chinese Journal of Computers · 2008
New event detection is an important research in the field of topic detection and tracking, and its task is real-time monitoring the stream of news stories and identifying the new topics in it. Current methods match the topics and stories as they are single-structured vectors of terms, which make the subtopics become noises of each other, and these noises often describe wrong semantics, by which the identification of new topics would be misled. In response to this defect, this paper proposes a new event detection method based on division comparison of subtopics, which divided each topic and story into different subtopics and identified new topic basing on the proportion and distribution relations of the relevant subtopics. This method achieves substantial improvement on TDT4 and TDT5, whose minimum cost of detection error is 0.4061 and missing probability is 0.1859.