Abstract
The popularization of the service-oriented manufacturing mode makes increasing customers configure the required manufacturing services from Industry Internet platforms. However, most recommendation methods mainly focus on the QoS indicators of the overall manufacturing service combination without considering the collaboration relationship between manufacturing services. A novel multi-attribute recommendation method of manufacturing service combination considering the historical collaboration relationship of the online platforms is studied in this paper. First, an evaluation indicator named manufacturing service collaboration frequency indicator (CFI) is introduced, which uses an improved machine learning algorithm combining FP-growth and Simrank to mine the frequent terms and similarities of the manufacturing service collaboration process. Then, a multi-objective evolutionary algorithm considering CFI and QoS is proposed to recommend a more reliable combination of manufacturing services for customers. Finally, comparative experiments are conducted to demonstrate the effectiveness and practicability of our method.
Published Version
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