Improved PageRank Algorithm Based on User Behavior and Topic Similarity in Microblog Environment

Aiming at the theme drifting and the page weight splitting of traditional PageRank algorithm,an improved PageRank algorithm is proposed.In order to improve the user query efficiency and search quality,combined with the time feedback factor,it makes a comprehensive analysis on user forwarding,user comments and micro-blog mentions.Statistical analysis is used to measure the contribution of user behavior in the ranking of micro-blog user influence.By using the improved TF-IDF algorithm to calculate the similarity weight of the topic,the user can select the Web page with high relevance to obtain the corresponding PageRank weight.Experimental results show that compared with common microblog ranking algorithms,the improved PageRank algorithm has better user influence ranking effect.

# Computer engineering. Computer hardware # Computer software # pagerank algorithm|similarity weight|time feedback factor|user behavior|random walk model

ZHU Haodong,DING Wenxue,YANG Lizhi,FENG Jiamei (2017). "Improved PageRank Algorithm Based on User Behavior and Topic Similarity in Microblog Environment". Jisuanji gongcheng. https://doi.org/10.3969/j.issn.1000-3428.2017.05.029