In order to improve the Resource Recommendation and sharing ability of mobile library, an intelligent optimization model of Mobile Library Resource Recommendation Service Based on digital twin technology is proposed. Build the association rule feature distribution set of mobile library resource recommendation service, carry out text information retrieval in the process of Mobile Library Resource Recommendation and sharing, carry out semantic correlation feature registration according to the retrieval preference of mobile library reading user object, establish the association rule data set of mobile library reading user object preference for mobile library Resource Recommendation and sharing, carry out feature block processing, and analyze the library reader preference. Complete the collaborative filtering recommendation of Mobile Library Resource Recommendation sharing. The simulation results show that the collaborative recommendation under the intelligent optimization mode of mobile library resource recommendation service using this method has high accuracy and good confidence level, which improves the intelligent level of Mobile Library Resource Recommendation and user satisfaction.

Abstract-The current automobile aftermarket of China is developing with a high speed, while the integration and expansion of chain enterprises are becoming more and more serious. This paper starts from the present situation of Chinese automobile aftermarket; analyzes the demand of competitive intelligence of chain enterprises during the integration and expansion process; put forward that during the integration and expansion process, chain enterprises of Chinese after-service market should focus on the establishment of competitive intelligence system, the competition and cooperative partnership, and the monitoring of the supply chain and groups.