Adaptive Chinese Topic Tracking Based on Feedback Learning
Huizhen Wang · Zhongwen xinxi xuebao · 2006
In the field of topic detection and tracking,since topics develop dynamically,topic excursion problem may appear in the tracking process.To overcome this problem and the shortcomings of current adaptive methods,we propose a new adaptive method based on feedback learning.Based on the idea of increment learning,the paper presents a new algorithm for the adaptive learning mechanism in the task of topic tracking.This algorithm can solve the problem of topic excursion,and remedy the deficiency of current adaptive methods.Time sequence of topic tracking task is also considered in the algorithm,and time information is introduced.In the experiments,we use the Chinese part in TDT4 corpus as test corpus,and use the TDT2004 evaluation metric to evaluate the adaptive Chinese topic tracking system based on feedback learning.The experimental results show that the adaptive method based on feedback learning can improve the performance of topic tracking.