大数据下基于信息流的快速种子用户识别  

Precise Identification of Seed Users Based on Information Flow in Big Data

作　　者：谢杨晓洁 赵凌[1] 

机构地区：[1]四川师范大学数学与软件科学学院,成都610066

出　　处：《计算机科学》2016年第7期281-284,共4页Computer Science

基　　金：国家自然科学基金重大研究计划:可信网络交易软件系统试验环境与示范应用(91218301);四川省教育厅重点项目:基于三阶段DEA方法对我国地区R&D投入绩效的评估及四川省R&D投入绩效分析(13sa0137)资助

摘　　要：针对大数据下的种子用户的精准识别,分析了影响用户成为种子用户的两大因素:时间优先和属性特征,以及种子信息传播的两大特征:传播时差和方向性。据此,提出了一种快速寻找种子用户的方法,即先将用户按属性特征分到不同的组中,通过分析所有组之间短信流通关系和传播时差找到信息流,即方向性,从而逐步缩小了搜索范围,再通过阈值筛选备选种子。最后验证备选种子,建立树状评价模型,设计种子用户的评价体系,由评价体系的最后得分寻找出种子用户。Aiming at the precise identification of data seeds under big data,we analyzed two major factors which impact users to become seeds users： time priority and attribute characteristics, and two characteristics of the dissemination of seed information：propagation time difference and directionality. Accordingly,we proposed a method to quickly find the seed users. First, users are put into different groups by the property features. Through analyzing the time difference and SMS circulation among all groups, we can find out the dissemination of information flow, that is to say, direction. Thus the search range is gradually narrowed, and alternative seed is filtered through threshold. We established evaluation model tree, designed seed users evaluation system, and used this evaluation system to calculate the final score to find out the seed users.

关 键 词：大数据 种子用户 信息流 信息流浓度 树状评价模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]