Zhiyong Wu, Ke Meng, Xiukun Yan, Dayin Shi, Benjia Hu
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Abstraction Refinement Approach for Web Service Selection using Skyline Computations
In this paper, we address the problem of time and space overload in large-scale web service selection. According to user needs, determine a workflow specifying a set of ordered tasks, and each task has a varying number of candidate services providing the basic functions to complete the task and some other subsidiary functions, The goal of service selection is to select the most eligible service for each task. However, with the development and popularization of the Internet, the number of Web services has shown exponential growth. Choosing among a large number of Web services has once again become a research hotspot. In this work, we use Skyline technology to initially filter many candidate services, and then use abstraction refinement technology to complete services selection. Experiments show that compared with the original method, our approach can show significant performance advantages in terms of time.