关键词: 用户需求挖掘, 云制造服务, 区块链, 联邦学习, 隐狄利克雷分布

Abstract: In the cloud manufacturing service scenario,service composition developers often need to develop customized service compositions based on users' manufacturing needs.With the prevalence of privacy protection laws and regulations,it has been difficult to implement commonly used user demand mining algorithms such as LDA topic model in practice.Through the cross-study of blockchain and federated learning technologies for user demand mining,a Decentralized Federated Latent Dirichlet Allocation algorithm (DAFedLDA) was proposed.In DAFedLDA,a Multi-Channel Access Control Scheme (MCACS) and a Random-Dropout Data Monitor Scheme (RDDMS) were presented based on the peer-to-peer distributed LDA.On the basis of the ProgrammableWeb.com dataset,a series of experiments demonstrated the effectiveness of the proposed algorithm.

Key words: user demand mining, cloud manufacturing service, blockchain, federated learning, Latent Dirichlet allocation