论文标题
使用基于指标的模型来检测人工智能科学生态系统中的新兴技术
Detecting Emerging Technologies in Artificial Intelligence Scientific Ecosystem Using an Indicator-based Model
论文作者
论文摘要
由于其潜在影响社会的潜在影响，对紧急话题的早期识别至关重要。有许多用于检测新兴术语和主题的方法，所有方法都具有优势和缺点。但是，关于出现的属性和指标尚无共识。在这项研究中，我们使用一种评估出现的新方法评估了人工智能领域中新兴的主题检测。我们还介绍了协作和技术影响的两个新属性，可以帮助我们同时使用纸张和专利信息。我们的结果证实，提出的新方法可以成功识别研究期间的新兴主题。此外，这种新方法可以为我们提供每个属性和最终出现分数的分数，这使我们能够以其出现分数和每个属性分数对新兴主题进行排名。
Early identification of emergent topics is of eminent importance due to their potential impacts on society. There are many methods for detecting emerging terms and topics, all with advantages and drawbacks. However, there is no consensus about the attributes and indicators of emergence. In this study, we evaluate emerging topic detection in the field of artificial intelligence using a new method to evaluate emergence. We also introduce two new attributes of collaboration and technological impact which can help us use both paper and patent information simultaneously. Our results confirm that the proposed new method can successfully identify the emerging topics in the period of the study. Moreover, this new method can provide us with the score of each attribute and a final emergence score, which enable us to rank the emerging topics with their emergence scores and each attribute score.
