Titlebook: Web Services – ICWS 2022; 29th International C Yuchao Zhang,Liang-Jie Zhang Conference proceedings 2022 The Editor(s) (if applicable) and T

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Yuchao Zhang,Pengmiao Li,Peizhuang Cong,Huan Zou,Xiaotian Wang,Xiaofeng Heinable AI systems. The literature study also revealed that most of the proposed solutions have not been evaluated in real projects, and there is a need for empirical studies. . For researchers, the study provides an overview of the candidate solutions and describes research gaps. For practitioners,

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he analyst who performed the interview and another reviewer. The idea is to use the identified cases of ambiguity to create questions for the follow-up interviews. Our empirical evaluation of this protocol involves 42 students from Kennesaw State University and University of Technology Sydney. The s

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,A Novel Outlier-Tolerable and Predictive Approach to Web Service Composition,nt estimation-based outlier detection method and a niched genetic algorithm. To validate the effectiveness of our proposed method, we conduct extensive case studies based on different outlier conditions, and the experimental results show that our method is superior to existing ones.

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,A Novel Outlier-Tolerable and Predictive Approach to Web Service Composition,nt estimation-based outlier detection method and a niched genetic algorithm. To validate the effectiveness of our proposed method, we conduct extensive case studies based on different outlier conditions, and the experimental results show that our method is superior to existing ones.

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,Towards an Improved Bi-GAN-Based End-to-End One-Class Classifier for Anomaly Detection in Cloud Dat-class Classifier (BG-HA-OC) is developed optimizing a one-class classifier and an anomaly scoring function. The Generator-Encoder-Discriminator Bi-GAN is capable of performing practical anomaly score computation and capturing fine temporal features. In the empirical study, we demonstrate that our p

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