摘要
随着定位技术的蓬勃发展,位置相关数据量呈指数式增长,其中数据劣质的问题日益显著。数据质量是统计工作的核心。轨迹大数据在各行各业应用渗透性不断扩大,确保轨迹大数据的可靠性、准确性和及时性,才能做出合理的决策,大数据的机遇和优势才能充分得到发挥。基于此,文章构建了大数据背景下签到轨迹数据质量的影响因素指标模型,利用真实的签到数据集,分析了影响签到轨迹数据质量的影响因素,并提出了提高签到轨迹数据质量的对策和方法。
With the rapid development of positioning technology, the amount of location-related data increases exponentially,and the problem of data inferiority is becoming more and more obvious. Data quality is the core of statistical work. The application permeability of trajectory big data in all walks of life is constantly expanding. Thus only when the reliability, accuracy and timeliness of trajectory big data can be guaranteed can reasonable decisions be made and full play to the opportunities and advantages of big data be given. Based on this, this paper constructs an index model of influencing factors on the quality of check-in trajectory data under the background of big data, and then analyzes the influencing factors on the quality of check-in trajectory data by using the real check-in data set. Finally, the paper proposes some countermeasures and methods to improve the quality of check-in trajectory data.
作者
潘晓
马昂
Pan Xiao;Ma Ang(School of Economics and Management,Shijiazhuang Tiedao University,Shijiazhuang 050043 China)
出处
《统计与决策》
CSSCI
北大核心
2019年第24期19-23,共5页
Statistics & Decision
基金
国家自然科学基金资助项目（61303017）
河北省自然科学基金资助项目（F2018210109）
河北省教育厅青年基金项目（ZD2018040）
石家庄铁道大学第四届优秀青年科学基金项目（Z661250444）
石家庄铁道大学研究生创新资助项目（YC201718）
关键词
签到轨迹数据
数据质量
大数据
check-in trajectory data
data quality
big data
