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基于灰色模型的端口短信预测和垃圾短信治理研究 被引量:1

Research on Port SMS Prediction and Spam SMS Governance Based on Grey Model
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摘要 根据对近年来手机短信和垃圾短信有关数据进行分析,显示端口短信越来越活跃,通过对端口信息和垃圾短信最主要的构成部分商业广告短信息进行相关分析,得出两者具有明显的正相关性。以官方公布的2014-2017年端口短信数量为研究对象,通过构建灰色模型预测我国未来几年内的端口短信将持续增长,商业广告类端口短信将成为垃圾短信治理的重点领域,并提出了垃圾短信预测和治理建议。 According to the data analysis related to mobile phone short message(SMS)and spam SMS in recent years,it is shown that the port SMS is becoming increasingly active.Through the correlation analysis between the port SMS and the commercial advertising SMS(i.e.,the major component of spam SMS),it is concluded that they have obvious positive correlation.Taking the officially announced number of port SMS in 2014-2017 as the research object,a gray model is established to predict that the port SMS will continue to grow in the next few years in China and the commercial port SMS will become the major area of spam SMS governance.Hence,some recommendations are proposed for spam SMS prediction and governance.
作者 杨光永 王雷 曾剑秋 YANG Guangyong;WANG Lei;ZENG Jianqiu(School of Economics&Management,Beijing University of Posts and Telecommunications,Beijing 100876,China;School of business,Guilin University of Electronic Science and Technology,Guilin 541004,China)
出处 《移动通信》 2021年第3期108-112,共5页 Mobile Communications
基金 国家社科基金重点项目(15ZDB154)。
关键词 垃圾短信 端口短信 相关分析 灰色模型 spam SMS port SMS correlation analysis gray model
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  • 1刘双,李海龙.用差分方程模型模拟北京2003年SARS疫情[J].生物数学学报,2006,21(1):21-27. 被引量:11
  • 2邓的荣.胡启恒:有限实名锻造负责任大国网民[J].科学新闻,2007(1):2-2. 被引量:3
  • 3Wang Y F. Predicting Stock Price Using Grey Prediction System[J]. Expert Systems with Applications, 2002,22(8).
  • 4Xie N M, Liu S K Discrete Grey Forecasting Model and Its Optimization[J]. Applied Mathematical Modelling, 2009,33 (4).
  • 5Li D C, Yeh C W, Chang C J. An Improved Grey--Based Approach for Early Manufacturing Data Forecasting[J]. Computers & Industrial Engineering, 2009, 57(5).
  • 6Dang Y G, Liu S F. The GM Models that x(n) be Taken as Initial Value[J]. Kybernetes, 2004, 33(2).
  • 7姚天祥,刘思峰.改进的离散灰色预测模型[J].系统工程,2007,25(9):103-106. 被引量:38
  • 8程少华,傅丁根.网络监督:蓬勃中呼唤规范[J].法制与社会.2009(5):6-8.
  • 9中国科学技术法学会.互联网企业个人信息保护测评标准[J].网络法律评论,2013,17(2):4-9.
  • 10Gross R, Acquisti A. Information revelation and privacy in online social networks [C]. NewYork: Proceedings of the 2005 ACM workshop on Privacy in the electronic society, 2005 : 71 -80.

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