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Reviewing and Predicting Human-Machine Cooperation Based on Knowledge Graph Analysis

机译：基于知识图分析的审查和预测人机合作

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Human-Machine Cooperation involves multiple fields and disciplines such as automated vehicles, robots, machine manufacturing, psychological cognition, and artificial intelligence. As research in these areas progresses rapidly, it is important to keep up with new trends and key turning points in the development of collective knowledge. Based on the visualization method, we can quickly sort out the ins and outs of this field in the vast literature and search for valuable and potential literature. First, we introduced the principles of scientific visualization of knowledge graphs. Then we extracted 3257 articles from Web of Science Core Collection and established a research field of bibliographic records of representative data sets. Next, we carried out a visual analysis of the discipline Dual-Map overlay, Co-words, Co-citation, and reviewed some key Highly-Cited documents. Finally, we summarize and analyze the literature with high betweenness central-ity, citation bursts, and Sigma value. This review will help professionals to have a more systematic understanding of the entire field and find opportunities for future Human-Machine Cooperation development.
机译：人机合作涉及多个领域和学科，如自动车辆，机器人，机器制造，心理认知和人工智能。随着这些领域的研究迅速发展，在集体知识的发展中跟上新的趋势和关键转折点是重要的。基于可视化方法，我们可以在广大文献中迅速整理该领域的INS和出局，并寻求有价值和潜在的文献。首先，我们介绍了知识图表的科学可视化原则。然后我们从科学核心系列网上提取了3257篇文章，并建立了代表数据集的书目记录的研究领域。接下来，我们对学科双层覆盖，合作，共同引文进行了视觉分析，并审查了一些关键的高度引用文件。最后，我们总结和分析了高度中央，引文爆发和西格玛价值之间的文献。该评论将帮助专业人士对整个领域的了解，并为未来的人机合作开发提供机会。

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