Abstract:

The paper proposed a page ranking algorithm based on PCM clustering algorithm in order to solve the problems that the topic relevance of search results are easily ignored and the topics are easily changed in the traditional page sorting algorithms. It improves the topic relevance of the search results and reduces the topic drift. Firstly, by inquiring a theme, random walk method (RWM) is used to calculate the two pages of the symmetrical social distance (SSD) between two web pages. Secondly, SSD and PCM clustering algorithm are used to cluster page and get each community of related topic, and obtain the probability of each member in every community group. Finally, according to the probability and recommended degree of the pages, the web pages are sorted. The experimental results show that, compared with the PageRank algorithm, the proposed page sorting algorithm based on PCM clustering algorithm can obtain a search result with more relevant topic. Because it targets a subject sort, the algorithm reduces the topic drift.     

Key words: ranking algorithm;RWM;SSD;PCM clustering algrithm