首页|New Machine Learning Findings from Blekinge Institute of Technology Described (Bibliometric Mining of Research Trends in Machine Learning)
New Machine Learning Findings from Blekinge Institute of Technology Described (Bibliometric Mining of Research Trends in Machine Learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Mdpi
New study results on artificial intelligence have been published. According to news reporting from Karlskrona, Sweden, by NewsRx journalists, research stated, “We present a method, including tool support, for bibliometric mining of trends in large and dynamic research areas. The method is applied to the machine learning research area for the years 2013 to 2022.” Financial supporters for this research include Knowledge Foundation in Sweden Through The Project “green Clouds-load Prediction And Optimization in Private Cloud Systems”. The news editors obtained a quote from the research from Blekinge Institute of Technology: “A total number of 398,782 documents from Scopus were analyzed. A taxonomy containing 26 research directions within machine learning was defined by four experts with the help of a Python program and existing taxonomies. The trends in terms of productivity, growth rate, and citations were analyzed for the research directions in the taxonomy. Our results show that the two directions, Applications and Algorithms, are the largest, and that the direction Convolutional Neural Networks is the one that grows the fastest and has the highest average number of citations per document. It also turns out that there is a clear correlation between the growth rate and the average number of citations per document, i.e., documents in fast-growing research directions have more citations. The trends for machine learning research in four geographic regions (North America, Europe, the BRICS countries, and The Rest of the World) were also analyzed.”
Blekinge Institute of TechnologyKarlskronaSwedenEuropeCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
Mdpi
