grouped and considered as single keywords.
Another innovative method was “word clusteranalysis”, combining and analyzing “words in title”, “author keywords”, and “KeyWords Plus”. This was used to discover the research trend, or “research hotspots
which students consider the predictions of human capital theory. Additionally, we create groups from students by clusteranalysis based on the examined 10 motivations. The analysis of motives is followed by an investigation of students' capital
The use of the cluster analysis in scientometrics is dealt with. The ways of developing citation networks and mapping research field with the help of this method are also presented. The methodology of computer-aided cluster analysis of citation is described, which allows to map the structure of a research field and to identify main tendencies of its development.
Authors:Xiaoyan Xing, Yanling Zhao, Weijun Kong, Yanwei Zhong, Dan Yan, Ping Zhang, Yumei Han, Lei Jia, Cheng Jin, and Xiaohe Xiao
.0 (SAS, USA).
Hierarchical clusteringanalysis (HCA)
The HCA is a chemometric method that is used to sort samples into groups and typically illustrated by a dendrogram [ 17 – 19 ]. This technique classifies
Authors:Dan Gao, Chong Woon Cho, Le Ba Vinh, Jin Hyeok Kim, Young Ho Kim, and Jong Seong Kang
Hierarchical ClusteringAnalysis (HCA), Principal Component Analysis (PCA), and Partial Least Square Discriminate Analysis (PLS-DA), were conducted to screen the characteristic components as chemical indicators for assessing the quality of fermented trifoliate
Authors:Silvia Ronzitti, Emiliano Soldini, Vittorio Lutri, Neil Smith, Massimo Clerici, and Henrietta Bowden-Jones
at a bivariate level. The Mann–Whitney test has been used to account for potential non-normality of the continuous variables. Second, we conducted a clusteranalysis: such analysis allows to partition the sample of patients in different subgroups