基于心理行为大数据分类算法的家政服务人员的专业性研究

Professionalism of Household Service Personnel Based on Psychology and Behavior Big Data Classification Algorithm

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%。

Abstract: 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%.