基于最长公共子序列的微博谣言溯源研究
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摘要
手机等移动设备的普及,使得微博等社交网络成为信息发布和共享的重要渠道。但同时,大量的反动、虚假、色情信息充斥着整个网络,谣言的恶劣影响日益突出,一些谣言的出现已经严重影响了人们对网络信息的获取和正常使用。如何对网络中的各类谣言进行检测,挖掘出谣言的源头及传播方式成为当前公安网信部门亟需解决的问题。本文以微博谣言为例,根据现有的LCS最长公共子序列算法在构造序列表格时做了相应的改进,并根据改进的LCS算法比对分析微博谣言。初步实验表明,改进后的算法可以更高效地对微博谣言进行比对溯源,从而帮助公安机关发现微博谣言源头。
Mobile phones and other mobile devices,make micro-blog and other social networks become an important channel for information dissemination and sharing. But at the same time,a large number of reactionary,false and pornographic information filled the entire network,and the rumors of the increasingly prominent adverse effects. Furthermore,the emergence of some rumors has seriously affected people's access to network information and normal use. How to detect all kinds of rumors in the network,and to find out the source of the rumor and the way of communication has become an urgent problem for public security network department to be solved. Micro-blog rumors,for example,according to the existing longest common subsequence( LCS) algorithm,the corresponding improvement is made in the construction of sequence table. The preliminary experiments show that the improved algorithm can be more efficient to compare and originate micro-blog rumors,so as to help public security network department to find the source of micro-blog rumors.
Mobile phones and other mobile devices,make micro-blog and other social networks become an important channel for information dissemination and sharing. But at the same time,a large number of reactionary,false and pornographic information filled the entire network,and the rumors of the increasingly prominent adverse effects. Furthermore,the emergence of some rumors has seriously affected people's access to network information and normal use. How to detect all kinds of rumors in the network,and to find out the source of the rumor and the way of communication has become an urgent problem for public security network department to be solved. Micro-blog rumors,for example,according to the existing longest common subsequence( LCS) algorithm,the corresponding improvement is made in the construction of sequence table. The preliminary experiments show that the improved algorithm can be more efficient to compare and originate micro-blog rumors,so as to help public security network department to find the source of micro-blog rumors.
引文
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[2]刘倩倩.微博在线社交网络的病毒传播研究[D].兰州:兰州交通大学,2015.
[3]Cha M,Haddi H,Benevenuto F,et al.Measuring user influence in Twitter[J].Pergamon Press,Inc.,2016,52(5):949-975.
[4]米昂.结合影响力分析的微博舆情溯源研究[D].北京:北京交通大学,2015.
[5]彭朝君.基于复杂社交网络的谣言传播和溯源模型[D].成都:西南交通大学,2016.
[6]陈卫哨.微博突发事件检测及溯源技术研究[D].哈尔滨:哈尔滨工程大学,2014.
[7]杨静,董圆,张健沛.一种基于话题影响力的微博话题溯源方法[J].小型微型计算机系统,2015,36(9):1939-1942.
[8]刘岗.基于微博事件的话题溯源方法[D].哈尔滨:哈尔滨工程大学,2015.
[9]廖慧芬,邵小兵.动态规划算法的原理及应用[J].中国科技信息,2005(21):42.
[10]李少芳,陈德礼.最小代价归并树的动态规划实现[J].太原师范学院学报(自然科学版),2007,6(3):120-123.
[11]胡婕.LCS及其变体问题的算法研究[D].南京:南京林业大学,2010.
[12]李欣,舒风笛.最长公共子序列问题的改进快速算法[J].计算机应用研究,2000,17(2):28-30.
[13]冯林,于孝航,孙焘,等.基于最长公共子序列距离的主旨模式挖掘算法[J].计算机工程,2008,34(14):47-48.
[14]贾志先.最长公共子序列算法在文字录入测试中的应用[J].计算机与现代化,2007(1):112-114.
[15]彭渊.基于内容的跨语言网页去重研究[D].哈尔滨:哈尔滨工业大学,2005.
[16]刘嘉怡.生物信息学多序列比对算法研究[D].成都:电子科技大学,2009.
[17]徐国华.拓展的LCS算法展开的网页关键词挖掘研究[J].湘潭大学自然科学学报,2015,37(1):107-110.
[18]Elias A,Khodja M D.Frequency of occurrence of LCS per cascade in BCC iron by PKA energy 30 ke V[J].Physics Procedia,2009,2(3):1489-1493.
[19]李磊.虚拟教学实验方案相似度的分析和度量[D].武汉:华中科技大学,2009.
[20]Landau G M,Levy A,Newman I.LCS approximation via embedding into locally non-repetitive strings[J].Information&Computation,2009,209(4):705-716.
[21]朱鲲鹏,魏芳.基于用户日志挖掘的查询扩展方法[J].计算机应用与软件,2012,29(6):113-117.
[22]时国华,周斌,韩毅.一种微博事件源头发现的方法[C]//第27次全国计算机安全学术交流会论文集.2012:146-149.