Affiliation:
1. Department of Computer and Information Science, University of Macau, Macau, China
2. College of Computer Science and Technology, Guizhou University, Guiyang, China
Abstract
Notwithstanding the advancement of service computing in recent years, service composition is still main issue in this field. In this paper, the authors present an integrated framework for semantic service composition using answer set programming. Unlike the AI planning approaches of top-down workflow with nested composition and combining composition procedure into service discovery, this proposed framework integrates designed workflow with nested composition. In addition, the planning is based on interface variables with validation through pre and post conditions. Moreover, a unified implementation of service discovery, selection, composition and validation is achieved by answer set programming. Finally, the framework performance is demonstrated by a travel booking example on QWSDataset.
Subject
Computer Networks and Communications,Information Systems,Software
Cited by
3 articles.
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1. Multi-Label Web Service Classification Using Neural Networks;2023 IEEE International Conference on Control, Electronics and Computer Technology (ICCECT);2023-04-28
2. ServeNet: A Deep Neural Network for Web Services Classification;2020 IEEE International Conference on Web Services (ICWS);2020-10
3. Deep Learning for Web Services Classification;2019 IEEE International Conference on Web Services (ICWS);2019-07