Electronic Science and Technology ›› 2022, Vol. 35 ›› Issue (11): 58-63.doi: 10.16180/j.cnki.issn1007-7820.2022.11.009

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Research Progress of Service Composition Based on Machine Learning

ZHANG Ye1,BAO Liang2   

  1. 1. The 30th Research Institute of China Electronic Technology Group Corporation,Chengdu 610041,China
    2. School of Computer Science and Technology,Xidian University,Xi'an 710071,China
  • Received:2021-04-16 Online:2022-11-15 Published:2022-11-11
  • Supported by:
    National Key R&D Program of China(2018YFC0831200);Natural Science Foundation of Shannxi(2019JM-368)


Service composition is a classic research problem in the field of service computing, which has received extensive attention in both industrial and academic fields. With the increasing popularity of cloud-native and micro-service technologies, a series of innovative researches have emerged in the field of service composition. With the rapid development of computer technology and artificial intelligence, machine learning algorithms such as deep learning and reinforcement learning are increasingly applied to traditional service composition problems. This study introduces the common classification and challenges of service composition problems, and summarizes the application of machine learning algorithms emerging in service composition problems in recent years. Additionally, the proposed study also summarizes the problems faced in the direction of solving service composition problems based on machine learning algorithms, and looks forward to the future development direction.

Key words: machine learning, deep learning, reinforcement learning, artificial intelligence, service composition, portfolio optimization, services computing, quality of service

CLC Number: 

  • TP389.1