﻿ 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

Service Science and Management
Vol. 09  No. 01 ( 2020 ), Article ID: 33733 , 9 pages
10.12677/SSEM.2020.91005

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

Yongwei Li, Fengtao Liu

Glorious Sun School of Business and Management (GSSBM), Donghua University, Shanghai

Received: Dec. 10th, 2019; accepted: Dec. 24th, 2019; published: Dec. 31st, 2019

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%.

Keywords:Household Services, Psychology and Behavior, Static Attributes, Big Data Classification, Naive Bayesian Algorithm

Copyright © 2020 by author(s) and Hans Publishers Inc.

1. 引言

2. 基于心理行为学实验的静态属性确定

2.1. 实验对象

Y企业家政服务人员。

2.2. 方法

1) 抽样调查

2) 调查方法

2.3. 统计分析

2.4. 调查结果

1) 实验一致性分析

2) 基本信息分析

2.5. 实验分析

1) 适应性分析

2) 满意度分析

2.6. 入户服务人员适应性和满意度相关因素分析

Table 1. Basic information of the respondents

Table 2. Adaptability of household service personnel

Table 3. Household service personnel satisfaction

Table 4. Adaptability of different characteristics of household service personnel and scores of each dimension

Table 5. Satisfaction and scores of various dimensions of housekeeping waiters with different characteristics

3. 基于心理行为学的大数据分类算法的判别模型构建

3.1. 算法流程构建

1) 训练样本集为一个已知分类的待分类项集合，这个集合叫做训练样本集。

$\begin{array}{l}P\left({x}_{1}|{y}_{1}\right),P\left({x}_{2}|{y}_{1}\right),\cdots ,P\left({x}_{6}|{y}_{1}\right);\\ P\left({x}_{1}|{y}_{2}\right),P\left({x}_{2}|{y}_{2}\right),\cdots ,P\left({x}_{6}|{y}_{2}\right);\\ \text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}⋮\\ P\left({x}_{1}|{y}_{4}\right),P\left({x}_{2}|{y}_{4}\right),\cdots ,P\left({x}_{6}|{y}_{4}\right);\end{array}$

2) 在朴素贝叶斯算法中，待分类项的每个特征属性都是条件独立的，由贝叶斯公式

$P\left({y}_{i}|X\right)=\frac{P\left(X|{y}_{i}\right)P\left({y}_{i}\right)}{P\left(X\right)}$

3) 因为各特征值是独立的，所以有：

$\begin{array}{c}P\left(X|{y}_{i}\right)P\left({y}_{i}\right)=P\left({x}_{1}|{y}_{i}\right)P\left({x}_{2}|{y}_{i}\right)P\left({x}_{3}|{y}_{i}\right)\cdots P\left({x}_{n}|{y}_{i}\right)\\ =P\left({y}_{i}\right)\underset{j=1}{\overset{n}{\prod }}P\left({x}_{j}|{y}_{j}\right)\end{array}$

$P\left({y}_{i}\right)=\frac{|{y}_{i}|}{|D|}$

$P\left({x}_{j}|{y}_{i}\right)=\frac{|在训练样本为{y}_{i}时,{x}_{j}出现的次数|}{|{y}_{i}训练样本数|}$

3.2. 实验部分

1) 数据预处理

Table 6. Basic property list of domestic servants in Y enterprises (part)

2) 分类结果

Table 7. Discrimination accuracy of test data samples

4. 结论

1) 围绕入户服务人员的心理行为调研实验，确立影响入户服务人员心理行为活动的六个静态属性为性别、年龄、户籍、分数、婚姻和学历。入户服务人员的属性确立在此之前是通过资深管理者的经验定性考量，本文研究融合个体心理行为活动的科学实验，以数理统计分析来实现入户服务人员的属性确立。

2) 在基于心理行为的朴素贝叶斯算法中，测试样本的分类达到了67.5%的分类准确率，大数据分类算法在互联网家政服务企业中具有很好的应用，准确率较高且具备分类代表性。

Professionalism of Household Service Personnel Based on Psychology and Behavior Big Data Classification Algorithm[J]. 服务科学和管理, 2020, 09(01): 40-48. https://doi.org/10.12677/SSEM.2020.91005

1. 1. 商务部. 2017年中国家政服务行业发展报告[R]. 上海: 电子商务研究中心, 2017: 1-29.

2. 2. 赵康. 专业, 专业属性及判断成熟专业的六条标准[J]. 社会学研究, 2000(5): 30-39.

3. 3. Cordes, C.L. and Dougherty, T.W. (1993) A Review and an Integration of Research on Job Burnout. The Academy of Management Review, 18, 621-656.
https://doi.org/10.5465/amr.1993.9402210153

4. 4. Maslach, C., Schaufeli, W.B., Leiter, M.P., et al. (2001) Job Burnout. Annual Review of Psychology, 52, 397-422.
https://doi.org/10.1146/annurev.psych.52.1.397

5. 5. 陈伟杰. 层级嵌入与社会工作的专业性——以A市妇联专业社会工作服务试点为例[J]. 妇女研究论丛, 2016(5): 5-16.

6. 6. 俞国良. 社会转型: 心理健康服务与社会心理服务[J]. 黑龙江社会科学, 2017, 15(4): 433-439.

7. 7. 陈钆汝. 家庭综合服务中心专业性问题研究[D]: [硕士学位论文]. 长春: 吉林大学, 2017.

8. 8. 董立岩, 隋鹏, 孙鹏, 等. 基于半监督学习的朴素贝叶斯分类新算法[J]. 吉林大学学报(工学版), 2016(3): 884-889.