摘要
数据分析是将描述性的、诊断性的、预测性的和规定性的模型用于数据,来回答特定的问题或发现新的见解的过程。本文以百度搜索指数为平台,以"三门峡职业技术学院"为搜索关键词,利用网络爬虫软件截取2012-2017年6年中的百度热词周搜索点击次数,通过灰色预测模型分析得出年度对应时间周的周搜索次数预测方程,经与一元线性回归模型预测值对比后判决预测方程合理有效,预判出以后2个年度的关键词搜索次数。最后通过数据图表分析"三门峡职业技术学院"作为百度搜索关键词有着显著的时间特征:一是总搜索次数每年呈递增趋势,二是在一年内的各周峰谷值有着明显的起伏规律,结合百度指数平台对关键词的周期搜索分布进行分析,提出相应的应对方法。
Big-data analysis is a process of applying descriptive,diagnostic,predictive,and prescriptive models for data to answer specific questions or to find new insights.Taking Baidu search index as a platform,and＂Sanmenxia Polytechnic＂as search keywords,this paper uses Web crawler software to intercept the weekly searching number of Baidu hot words from 2012 to 2017.Through the grey prediction model,the weekly searching frequency prediction equation is obtained.Compared with the predicted value of an element linear regression model,it’s verified that the prediction equation is reasonable and effective,and the number of keywords searched in the next two-year is predicted.Finally,through data chart analysis,＂Sanmenxia Polytechnic＂as Baidu search keywords has significant time characteristics：firstly,the total number of search is increasing every year,secondly,the peak and valley value every week in a year has an obvious fluctuation law.Combined with Baidu search index platform to analyze the periodic search distribution of keywords,the corresponding countermeasures are put forward.
作者
李斌
吴庆涛
LI Bin;WU Qing-tao(Modern Educational Technology Center,College of Applied Engineering,Henan University of Science and Technology,Sanmenxia 472000,China;School of Information Engineering,Henan University of Science and Technology,Luoyang 471023,China)
出处
《计算机与现代化》
2018年第9期98-104,共7页
Computer and Modernization
基金
河南省教育厅高等教育教学改革与实践项目(2017SJGLX636)
