The nature of statistical learning theory
The nature of statistical learning theory
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Improving text categorization methods for event tracking
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
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Topic tracking, which starts from a few sample stories and finds all subsequent stories that discuss the same topic, is a new challenge for the text categorization task and is useful for timeline-based IR systems. Much previous research on topic tracking use machine learning techniques. However, the small size of the training data, especially positive training stories, presents difficulties in training the parameters of the topic tracking system to produce optimal results. In this paper, we present a method for topic tracking using subject templates and k-means clustering algorithm to select a suitable training set. The method was tested on the TDT1 corpus, and the result shows the effectiveness of the method.