@inproceedings{297e604114fd4a5287e7e8e1867c3b24,
title = "ServeNet: A Deep Neural Network for Web Services Classification",
abstract = "Automated service classification plays a crucial role in service discovery, selection, and composition. Machine learning has been widely 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 novel deep neural network to automatically abstract low-level representation of both service name and service description to high-level merged features without feature engineering and the length limitation, 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 in classification and more robust than other machine learning methods.",
keywords = "Deep Learning, Service, Service Classification, Service Discovery, Web Services",
author = "Yilong Yang and Nafees Qamar and Peng Liu and Katarina Grolinger and Weiru Wang and Zhi Li and Zhifang Liao",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 13th IEEE International Conference on Web Services, ICWS 2020 ; Conference date: 18-10-2020 Through 24-10-2020",
year = "2020",
month = oct,
doi = "10.1109/ICWS49710.2020.00029",
language = "英语",
series = "Proceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "168--175",
booktitle = "Proceedings - 2020 IEEE 13th International Conference on Web Services, ICWS 2020",
address = "美国",
}