Abstract
Scheduling analysis, which focuses on the evaluation, testing and verification of the scheduling systems and the algorithms used in real-time operations, is critical to a number of research areas such as databases and transaction management. In order to better understand the field of scheduling, we select and investigate 9,611 papers about scheduling from five SCI journals which have published many excellent papers about scheduling. This paper presents a collaboration analysis of the scheduling field. In addition, we generate three networks to analyze collaboration patterns between scientists, including co-authorship network, keyword co-occurrence network and author co-keyword network to show the collaboration relationship between authors in the field of scheduling. The research findings from our work can help researchers understand the research status of scheduling and gain valuable insights on future technical trends in the scheduling field.
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Acknowledgment
This work was supported in part by the Natural Science Foundation of China under Grant 61502069, by the Natural Science Foundation of Liaoning under Grant 2015020003.
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Xu, X., Liu, Y., Ma, R., Sheng, Q.Z. (2017). Collaboration Patterns at Scheduling in 10 Years. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2017. Lecture Notes in Computer Science(), vol 10451. Springer, Cham. https://doi.org/10.1007/978-3-319-66805-5_30
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DOI: https://doi.org/10.1007/978-3-319-66805-5_30
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