神经处理快报(Neural Processing Letters)是一本国际期刊,发表了人工神经网络各方面的研究成果和创新思想。涵盖范围包括理论发展,生物模型,新的形式模式,学习,应用,软件和硬件的发展,和前瞻性研究。该杂志促进了神经网络研究人员和用户之间信息的快速交流。自1980年代初以来,对人工神经网络领域的兴趣重新出现,与此同时,各专门或多学科小组也进行了大量的研究活动。 官网地址:http://dblp.uni-trier.de/db/journals/npl/

In this study, we investigate the extent to that patent citations to papers can serve as early signs for predicting delayed recognition using a comparative study with a control group, i.e., instant recognition papers. We identify the two opposite groups of papers by the Bcp measure, a parameter-free index for identifying papers which were recognized with delay (also called "sleeping beauties" in science). Combined with a typical case study, it appears that papers with delayed recognition show a stronger and longer technical impact than instant recognition papers. We provide indication that in the more recent years papers with delayed recognition are awakened more often and more earlier by a patent rather than by a scientific paper (also called "prince"). We also found that patent citations seem to play an important role to avoid instant recognition papers to level off or to become a so called "flash in the pan". It also appears that the sleeping beauties may firstly encounter negative citations and then patent citations and finally get widely recognized. In contrast to the two focus fields (biology and chemistry) for instant recognition papers, delayed recognition papers are rather evenly distributed in biology, chemistry, psychology, geology, materials science, and physics. We discovered several pairs of "science sleeping"-"technology inducing", such as biology-biotechnology/pharmaceuticals, chemistry-chemical engineering, psychology-computer/control technology, and physics-computer technology. We propose in further research to discover the potential ahead of time and transformative research by using citation delay analysis, patent & NPL analysis, and citation context analysis.

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