Applied research of text clustering algorithm in network monitoring public opinion
Lou Yun · Electronic Design Engineering · 2013
To meet the needs of topic detection for monitoring the public opinion on internet,this paper proposed an incremental clustering algorithm to improve the two main disadvantages of single-pass algorithm,that was,being easily effected by the order of inputs and low precision.In this paper,the single-pass clustering algorithm the average-1ink strategy and the introduction of the idea of generation in batches clustering inherited the simple principle from single-pass to ensure clustering internet texts in real time and overcame.Tough the experimental analysis of the improved single-pass algorithm than the single-pass algorithm in the miss rate,error rate and time consuming aspects has greatly improved.The experimental results show the improved algorithm in improving the topic detection accuracy on the validity and practicality.