基于K-均值聚类算法的众包任务定价模型设计

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英文篇名：Crowdsourcing Task Pricing Model Design Based on K-means Clustering Algorithm 作者：赵建君 ; 杨伟男 ; 虞赟泽 ; 蒋巍巍 英文作者：ZHAO Jianjun;YANG Weinan;YU Yunze;JIANG Weiwei;Zhejiang Chinese Medical University; 关键词：主成分分析法 ; 红细胞计数法 ; 循环遍历法 ; K-均值聚类 英文关键词：principal component analysis;;red blood cell counting;;loop traversal;;K-means clustering 中文刊名：XDXK 英文刊名：Modern Information Technology 机构：浙江中医药大学; 出版日期：2019-06-25 出版单位：现代信息科技 年：2019 期：v.3 语种：中文; 页：XDXK201912029 页数：3 CN：12 ISSN：44-1736/TN 分类号：80-82

摘要

针对众包任务的合理定价问题,首先将任务定价划分为区域间任务定价和区域内任务定价。其次针对区域间任务定价,运用K-均值聚类法划分任务区域;选择合理指标,建立基于主成分分析法的优化任务定价模型。针对区域内任务定价,确定会员中心及区域内任务定价与到会员中心距离的关系。最后通过循环遍历法得到众包任务定价方案。通过新定价方案与原方案的对比表明,该模型可以制定出准确、合理的任务定价方案。
        To solve the problem of reasonable pricing for crowdsourcing tasks. Firstly,divided it into inter-regional task pricing and intra-regional task pricing. Secondly,according to the inter-regional task pricing,the K-means clustering method is used to divide the task areas,and the optimal task pricing model based on principal component analysis is established by selecting reasonable indicators.Aiming at the task pricing in the region,the relationship between the task pricing in the member center and the distance from the member center is determined. Finally,the pricing scheme of crowdsourcing tasks is obtained by cyclic traversal method. The comparison between the new pricing scheme and the original one shows that the model can work out an accurate and reasonable task pricing scheme.

引文

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