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ASM-TL: an Abstract Service Model Enabling Adaptive Matchmaking.

, , , , and . ICEBE, page 559-562. IEEE Computer Society, (2007)

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ASM-TL: an Abstract Service Model Enabling Adaptive Matchmaking., , , , and . ICEBE, page 559-562. IEEE Computer Society, (2007)Enhancing Smart Re-run of Kepler Scientific Workflows Based on Near Optimum Provenance Caching in Cloud., , , and . SERVICES, page 378-384. IEEE Computer Society, (2014)Enhancing the MapReduce training of BP neural networks based on local weight matrix evolution., , , and . BigData, page 2829-2835. IEEE Computer Society, (2017)Business-Oriented Virtualization of Web Services A Case Study., , , , and . SOSE, page 275-280. IEEE Computer Society, (2008)Training Back Propagation Neural Networks in MapReduce on High-Dimensional Big Datasets With Global Evolution., , , , and . IEEE Access, (2019)Anomaly detection of high-dimensional sparse data based on Ensemble Generative Adversarial Networks., , , , , and . IEEE BigData, page 3042-3049. IEEE, (2021)An Approach to Service Adaptation for Exploratory Application Construction., , and . ANT/MobiWIS, volume 10 of Procedia Computer Science, page 909-914. Elsevier, (2012)Agile Services Oriented Virtualization of Web Services., and . TASE, page 153-160. IEEE Computer Society, (2012)Blockchain Based Provenance Sharing of Scientific Workflows., , , , , and . BigData, page 3814-3820. IEEE, (2018)Interpolation-based k-means Clustering Improvement for Sparse, High Dimensional Data., and . ICCBDC, page 11-15. ACM, (2019)