A Comparative Study between Single-Pass Algorithm and K-means Algorithm in Web Topic Detection

As with the extensive application of the Internet, the explosive growth of information and unpre cedented enthusiasm of users, the monitoring and management of Web content is becoming more and more imminent. Although traditional Single-Pass algorithm and K-means algorithm each ha s shortcomings, they are widely used in clustering analysis because of their relatively simple prin- ciples and fast computing speed. This paper firstly describes the overall flow of the entire topic of de tection, then we make a comparison between Single-Pass algorithm and K-means algorithm. In order to verify the comparison, finally, an experiment is designed. The result shows that Single-Pass a lgorithm is better than K-means algorithm in Web topic detection.