This work was supported in part by the National Key Research and Development Program of China under Grant No. 2017YFB1400602. To carry out the study of the online QoS (Quality of Service) prediction, we retrieved and collected a middle-size dataset of Web services. For researchers who are interested in this dataset, you can feel free to download and use it. Also, if you think that it is useful for your work, please help cite the following paper.
Ruibin Xiong, Jian Wang, Zhongqiao Li, Bing Li, and Patrick C.K. Hung. Personalized LSTM Based Matrix Factorization for Online QoS Prediction. In Proceedings of the 2018 IEEE International Conference on Web Services (ICWS 2018), pp. 34-41, 2018.
4500 x 140 x 64 time-aware Web service QoS dataset
This dataset describes real-world QoS evaluation results from 140 users on 4,500 Web services over 64 consecutive time slices (at 15-minute interval), which is created based on the raw observations of WSDream by removing users with extremely sparse data and adding side-information of users and services. Most of users and services have geographic location information (some of them may be inaccurate). The dataset can be retrieved by contacting Dr. Jian Wang (e-mail: jianwang@whu.edu.cn).