@inproceedings{532730c98a5643c1ab771d5bc5175029,
title = "Deep learning for web services classification",
abstract = "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.",
keywords = "Deep Learning, Service, Service Classification, Service Discovery, Web Service",
author = "Yilong Yang and Wei Ke and Weiru Wang and Yongxin Zhao",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 26th IEEE International Conference on Web Services, ICWS 2019 ; Conference date: 08-07-2019 Through 13-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICWS.2019.00079",
language = "英语",
series = "Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "440--442",
editor = "Elisa Bertino and Chang, \{Carl K.\} and Peter Chen and Ernesto Damiani and Ernesto Damiani and Michael Goul and Katsunori Oyama",
booktitle = "Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services",
address = "美国",
}