摘要
针对某劳务众包平台——拍照赚钱APP的任务定价,根据数据位置及分布的统计特征,充分挖掘所给数据信息,利用R软件,基于K-Means聚类算法计算出每一价格任务到聚类中心的最短距离,建立任务价格与距离的非线性回归模型.探讨任务的定价机制,发现任务的定价与其距聚类中心的距离存在幂函数关系,并提出了优化任务定价的建议.
Aims to the task pricing of a certain labor crowdsourcing platform——making money by taking pictures APP,according to the statistical characteristics of the location and distribution of data,fully mines the given data information,R software is used so as to calculate the shortest distance of each pricing task to the clustering center based on K-Means clustering algorithm.A regression model of the task price and distance is established to discuss the pricing mechanism of the task,the result is that the pricing of task has a power function with its distance to the cluster center.Ultimately,suggestions for optimizing task pricing are put forward.
作者
冯宜强
李春忠
FENG Yi-qiang;LI Chun-zhong(School of Finance;School of Statistics and Applied Mathematics,Anhui University of Finance and Economics,Bengbu 233030,Anhui)
出处
《高师理科学刊》
2018年第5期18-21,共4页
Journal of Science of Teachers＇College and University
基金
国家自然科学基金青年项目(61305070)
安徽财经大学金融学院大学生科研基金项目(JR201810)
