AbstractWith increasing number of enterprises involving in Cloud Manufacturing (CMfg), service reputation evalua'/> A hierarchical and configurable reputation evaluation model for cloud manufacturing services based on collaborative filtering
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A hierarchical and configurable reputation evaluation model for cloud manufacturing services based on collaborative filtering

机译:基于协作滤波的云制造服务分层和可配置的信誉评价模型

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AbstractWith increasing number of enterprises involving in Cloud Manufacturing (CMfg), service reputation evaluation is becoming important in CMfg service platform. Existing reputation evaluation methods have poor configurablity and low scalability, they also suffer greatly from data sparsity. In this paper, we present a collaborative filtering (CF)-based hierarchical and configurable reputation evaluation method. First, we propose a hybrid framework to deal with sparsity issue in user feedback data. Then, we establish a library of evaluation metrics and select corresponding metrics to build a reputation computation model. Finally, the feedback data is fed into the evaluation model to calculate service reputations. We conduct an experiment to verify the validity and efficiency of our method.]]>
机译:<![cdata [ <标题>抽象 ara>随着涉及云制造(CMFG)的企业数量,服务信誉评估 在CMFG服务平台中变得重要。 现有的信誉评估方法具有较差的配置和低可扩展性,它们也从数据稀疏性遭受了极大的影响。 在本文中,我们提出了一种基于协作滤波(CF)的分层和可配置的声誉评估方法。 首先,我们提出了一个混合框架来处理用户反馈数据中的稀疏问题。 然后,我们建立一个评估度量库,选择相应的度量来构建声誉计算模型。 最后,反馈数据被馈送到评估模型中以计算服务声誉。 我们进行实验以验证我们方法的有效性和效率。 ]]>

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