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Online labor service crowdsourcing analysis based on linear discriminant regression

机译:基于线性判别回归的在线劳务众包分析

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In order to enhance the effectiveness of the research on the new-type business management of online labour service crowdsourcing effect based on sharing economy, this paper proposes an online labour service crowdsourcing effect analysis method based on linear discriminant regression. Firstly, it relies on knowledge service and business combination to promote the selection coordination of public users and crowdsourcing website in sharing value-driving and spacial technology, wherein, the value chain of crowdsourcing is the value network composed of infrastructure and operation process, it promotes the communication technology product or technical service through the product flow, service flow, information flow and capital flow of value network and establishes the research model; secondly, based on linear discriminant regression, it measures and tests the relationship between online labour service crowdsourcing effect and single class by aid of the nearest subspace classifier, based on the relationship between test effect and training effect obtained from the farthest subspace classifier, finally, it verifies the effectiveness of the algorithm through simulated experiment. (C) 2018 Elsevier B.V. All rights reserved.
机译:为了提高基于共享经济的新型在线劳动服务众包效果企业管理研究的有效性,提出了一种基于线性判别回归的在线劳动服务众包效果分析方法。首先,它依靠知识服务和业务的结合,促进公共用户和众包网站在共享价值驱动和空间技术上的选择协调,其中,众包的价值链是由基础设施和运营过程组成的价值网络。通过价值网络的产品流,服务流,信息流和资金流对通信技术产品或技术服务进行研究,建立研究模型;其次,基于线性判别回归,基于最近的子空间分类器获得的测试效果与训练效果之间的关系,借助最近的子空间分类器对在线劳务众包效果与单一类之间的关系进行度量和测试,最后,通过仿真实验验证了算法的有效性。 (C)2018 Elsevier B.V.保留所有权利。

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