加入用户行为因素的BBS热点分析算法仿真  

Simulation of BBSHotspot Analysis Algorithm Based on User Behavior Factors

作　　者：张帆[1] 王艳杰[1] 

机构地区：[1]郑州经贸职业学院计算机系,郑州450044

出　　处：《科技通报》2014年第8期146-148,共3页Bulletin of Science and Technology

摘　　要：BBS热点挖掘是研究网络舆情传播影响力的重要手段。传统的BBS热点挖掘采用统计特征分析法,不能实现对BBS信息资源的全面覆盖,分析参量单一,热点特征挖掘不准确。提出一种对BBS用户转发评论和提及行为综合分析的BBS热点挖掘算法,建立了BBS热点影响力度量及用户行为综合分析数学模型,进行热点评价及影响力数学度量,实现BBS用户行为综合分析。实验表明采用该算法进行BBS热点跟踪挖掘,提高了BBS网页的召回率,避免出现冗余信息和中止检索,热点挖掘性能和准确度较传统方法提高显著,在网络舆情分析和BBS系统管理等领域具有很好的应用价值。BBS hot spot mining is an important means to study the influence of the network. Traditional BBS hotspot tradi-tional mining uses the statistical analysis method, it cannot achieve comprehensive coverage of BBS information resources, and the parameter is single, data mining is not accurate. An improved BBS hotspot information tracking and mining algo-rithm based on user behavior comprehensive analysis is proposed, and BBS hotspot influence metrics and user behavior analysis model is established. Simulation results show that the recall rate of BBS Webpage is improved, and redundant in-formation is avoided, the data mining accuracy is improved. It has good application value in the analysis of network public opinion and the BBS system management field.

关 键 词：BBS热点 用户行为特征 数据挖掘 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]