Deep learning for web services classification

Yilong Yang, Wei Ke, Weiru Wang, Yongxin Zhao

研究成果: Conference contribution同行評審

45 引文 斯高帕斯(Scopus)

摘要

Automated service classification plays a crucial role in service discovery, selection, and composition. Machine learning has been used for service classification in recent years. However, the performance of conventional machine learning methods highly depends on the quality of manual feature engineering. In this paper, we present a deep neural network to automatically abstract low-level representation of service description to high-level features without feature engineering and then predict service classification on 50 service categories. To demonstrate the effectiveness of our approach, we conduct a comprehensive experimental study by comparing 10 machine learning methods on 10,000 real-world web services. The result shows that the proposed deep neural network can achieve higher accuracy than other machine learning methods.

原文English
主出版物標題Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services
編輯Elisa Bertino, Carl K. Chang, Peter Chen, Ernesto Damiani, Ernesto Damiani, Michael Goul, Katsunori Oyama
發行者Institute of Electrical and Electronics Engineers Inc.
頁面440-442
頁數3
ISBN(電子)9781728127170
DOIs
出版狀態Published - 7月 2019
事件26th IEEE International Conference on Web Services, ICWS 2019 - Milan, Italy
持續時間: 8 7月 201913 7月 2019

出版系列

名字Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services

Conference

Conference26th IEEE International Conference on Web Services, ICWS 2019
國家/地區Italy
城市Milan
期間8/07/1913/07/19

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