用户行为数据分析下的信息推送系统的设计
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摘要
针对在信息推送过程中难以计算出用户行为数据分析下信息推送指标的权重输出,存在信息推送针对性差,信息推广转化率低的问题,提出一种基于模糊遗传的用户行为数据分析下的信息推送系统设计方法。将互联网用户抽象为结构化数据信息本体,计算出用户行为数据下各词汇的TF-IDF指标,建立用户行为数据下的行为-主题分布模型和主题-词汇分布模型,得到用户行为数据下所有主题-词汇的联合分布,利用向量模型匹配关键词思想理论确定关键词在文档中的权重,通过用户查询与结果记录词条间的关联性计算,得到用户行为数据下不同信息推送指标的权重输出,由此完成用户行为数据分析下的信息推送系统设计。实验结果表明该方法能够有效提高信息推送的准确性,且可扩展性较强。
The current method to push information is difficult to calculate the output weight of information push index under user behavior data analysis,and has poor pertinency and low percent conversion of information push. Therefore,a fuzzy genetic based design method of information push system under user behavior data analysis is proposed. The Internet users are abstracted as structural data information ontology by means of the method to calculate the TF-IDF index of each vocabulary under user behavior data. The behavior-theme distribution model and theme-vocabulary distribution model under user behavior data were established to get all theme-vocabulary joint distributions under user behavior data. The theory of vector model marching keyword is used to determine the weight of keyword in the file. The correlation between entries is calculated by means of user query and result recording to get the output weight of different information push indexes under user behavior data,so as to design the information push system under user behavior data analysis. Experimental results show that the method can improve the accuracy of information push effectively,and has strong scalability.
The current method to push information is difficult to calculate the output weight of information push index under user behavior data analysis,and has poor pertinency and low percent conversion of information push. Therefore,a fuzzy genetic based design method of information push system under user behavior data analysis is proposed. The Internet users are abstracted as structural data information ontology by means of the method to calculate the TF-IDF index of each vocabulary under user behavior data. The behavior-theme distribution model and theme-vocabulary distribution model under user behavior data were established to get all theme-vocabulary joint distributions under user behavior data. The theory of vector model marching keyword is used to determine the weight of keyword in the file. The correlation between entries is calculated by means of user query and result recording to get the output weight of different information push indexes under user behavior data,so as to design the information push system under user behavior data analysis. Experimental results show that the method can improve the accuracy of information push effectively,and has strong scalability.
引文
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[8]田林青,余成波,孔庆达,等.基于蓝牙技术的推送系统的设计和实现[J].微型机与应用,2016,35(20):61-64.
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[10]李欢.基于文化安全的微博信息推送技术的研究[J].现代电子技术,2016,39(8):41-44.
[2]邓志文,都平平,秦丽,等.面向社交网的图书馆信息主动推送方法研究:以“人人网”为例[J].图书馆杂志,2015,34(3):84-89.
[3]陈伶娜.移动新闻客户端信息推送特点及问题分析:以凤凰新闻、今日头条等五大新闻客户端为例[J].今传媒,2016,24(10):17-19.
[4]屈赟,陶晡,王克俭.基于Android的果树病虫害信息推送系统的设计[J].科技通报,2016,32(5):86-90.
[5]尹延宁,刘太君,叶焱,等.基于Node.js,Sencha Touch和i Beacon信息推送系统的设计与实现[J].火力与指挥控制,2016,41(8):151-154.
[6]路晔绵,李轶夫,应凌云,等.Android应用第三方推送服务安全分析与安全增强[J].计算机研究与发展,2016,53(11):2431-2445.
[7]杨帆,何敏,施继红,等.基于LDA模型的网络党建信息推送策略[J].计算机工程,2016,42(9):286-291.
[8]田林青,余成波,孔庆达,等.基于蓝牙技术的推送系统的设计和实现[J].微型机与应用,2016,35(20):61-64.
[9]方耀耀,李同刚.面向Android系统的内容推送方法应用研究[J].电脑知识与技术,2016,12(7):28-31.
[10]李欢.基于文化安全的微博信息推送技术的研究[J].现代电子技术,2016,39(8):41-44.