计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 203-.doi: 10.11896/jsjkx.200900024

• 大数据&数据科学 • 上一篇    下一篇

基于树增益朴素贝叶斯网络的服务定价策略

韩丽霞1, 张占营2   

  1. 1 天津市西青区人民检察院 天津300380
    2 天津师范大学计算机与信息工程学院 天津300387
  • 出版日期:2021-06-10 发布日期:2021-06-17
  • 通讯作者: 张占营(zhanying999666@163.com)
  • 作者简介:1984724553@qq.com

TAN-based Service Pricing Strategy

HAN Li-xia1, ZHANG Zhan-ying2   

  1. 1 The People's Procuratorate of Tianjin Xiqing District, Tianjin 300380, China
    2 College of Computer and Information Engineering,Tianjin Normal University,Tianjin 300387,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:HAN Li-xia,born in 1985,postgra-duate.Her main research interests include network security and so on.
    ZHANG Zhan-ying,born in 1984,Ph.D,lecturer,is a member of China ComputerFederation.His main research interests include iot and big data.

摘要: 移动劳务众包是一种新型商业模式。服务定价问题是劳务众包平台的核心问题,它与任务完成度和企业利润密切相关。针对移动互联网中劳务众包平台的定价问题,对历史数据进行建模,探究定价和影响因素。采用多元线性回归对价格的主要影响因素进行拟合,研究了用户拍照任务执行情况、任务地理位置与拍照任务定价之间的函数关系。基于分治思想,使用树增益朴素贝叶斯网络(TAN)将地理信息划分为5个区域,将每个任务执行点用元组{任务完成度,任务标价,经度、纬度,信誉度}表示,对散点进行聚类分析,分析了任务未完成原因以及任务位置对任务完成情况的影响。提出区域会员信誉度计算方法,分别计算每个区域的信誉度,由信誉度和地理位置导出不同区域的价格,并评价该方案的实施效果。

关键词: 定价策略, 树增益朴素贝叶斯网络, 众包

Abstract: Aiming at the pricing problem of labor crowd sourcing platform in mobile Internet,this paper uses multiple linear regression to fit the main influencing factors of price.Based on the idea of divide and conquer,the geographic information is divided into five regions by using tree gain naive Bayesian network (TAN).Through clustering analysis,the scattered points are clustered,and the regional member reputation calculation method is proposed,and each region is calculated separately.According to the credibility and geographical location,the prices of different regions are derived.The solution proposed in this paper has a certain reference significance to the pricing problem,which is greatly affected by geographic information.

Key words: Crowd sourcing, Pricing strategy, TAN

中图分类号: 

  • TP399
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