微博环境下基于用户行为与主题相似度的改进PageRank算法  

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

作　　者：朱颢东[1] 丁温雪 杨立志[1] 冯嘉美 

机构地区：[1]郑州轻工业学院计算机与通信工程学院,郑州450002

出　　处：《计算机工程》2017年第5期179-184,共6页Computer Engineering

基　　金：河南省科技计划项目(152102210149;152102210357);河南省高等学校青年骨干教师资助计划项目(2014GGJS-084);河南省高等学校重点科研项目(16A520030);郑州轻工业学院校级青年骨干教师培养对象资助计划项目(XGGJS02);郑州轻工业学院博士科研基金(2010BSJJ038)

摘　　要：针对传统PageRank算法存在主题漂移、网页权值均分等问题,提出一种改进的PageRank算法。为提高用户查询效率和搜索质量,结合时间反馈因子对用户转发、用户评论和微博提及行为进行综合分析,采用统计分析方法对用户行为在微博用户影响力排序中的贡献进行度量,并利用改进的TF-IDF算法计算主题相似度权值使用户能够选择相关度较高的网页,从而获得相对应的PageRank权值。实验结果表明,与微博常用排序算法相比,改进PageRank算法具有更好的用户影响力排序效果。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.

关 键 词：PAGERANK算法 相似度权值 时间反馈因子 用户行为 随机游走模型 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]