检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]东华大学旭日工商管理学院,上海
出 处:《服务科学和管理》2020年第1期40-48,共9页Service Science and Management
摘 要:本文为解决互联网家政服务业入户服务人员的专业性分类问题,基于Y互联网家政服务企业的详细入户服务人员数据库,运用心理行为的调研实验,确立入户服务人员的静态属性,进而提出了针对入户服务人员专业性的大数据分类算法的判别模型,在对入户服务人员的训练样本集进行判别模型的初步训练基础上,实现入户服务人员数据中测试样本集判别准确率的分析。研究结果显示,针对入户服务人员的心理行为,调研实验确立了研究的六个静态属性,分别是年龄、性别、籍贯、分数、婚姻、学历;基于心理行为学的大数据分类算法的判别模型对于入户服务人员的专业性分类准确率达到67.5%。This paper is to solve the attribute selection problem of the home service personnel in the Internet home service industry. Based on the detailed database of household service personnel of Y Internet home service companies, this paper establishes the static attribute of household service personnel by means of psychological behavior research experiments. Then, the discrimination model of big data classification algorithm for professional service personnel is proposed. Based on the preliminary training of the discriminant model of the training sample set of the household service personnel, the analysis of the accuracy of the test sample set in the data of the household service personnel is realized. The findings are as follows. Based on the theory of psychology and behavior, the survey of household service personnel established six static attributes of research: age, gender, household registration, score, marriage and education. The accuracy rate of the discriminant model of big data classification based on psychological behavior for the professionalism of the household service personnel reached 67.5%.
关 键 词:家政服务 心理与行为 静态属性 大数据分类 朴素贝叶斯算法
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.249