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of variety means using cluster analysis and dendrograms. Exp. Agricult. 25 :259–269. Christie B.R. Comparison of variety means using cluster analysis and dendrograms
methodological tools (partially ordered set (poset) and TDEA). Then in the following section (3), we introduce the poset, TDEA, and cluster analysis models used for evaluating the countries in our dataset and the main results, which are then compared to our
use, attachment style, sexual desire, and self-esteem – whether subgroups of Tinder users can be identified through cluster analysis. Compared to more traditional linear models such as regression, cluster analysis emphasizes the diversity among
worthwhile to render. In this context, by employing a clustering analysis with the Gaussian mixture model (GMM), we suggest an empirical framework to classify research collaboration activities with developed indicators that carry on the concept of previous
Abstract
Possible applications of cluster analysis of bibliographic references as a scientometric method are studied. It is shown that cluster analysis made by means of bibliographic coupling byKessler and co-citation byMarshakova-Small present comparable results. 
Science maps
on immunological topics are made. Particularly for historico-scientific studies it is useful to make clusters in rectangular coordinates taking into account the value of citing the document and the year of its publication. It is observed that at the junction points of sciences there is an almost twofold deceleration of the processes of application and spreading of knowledge. It is stated that the problem of information explosion does not exist on the level of new ideas, the number of which is less than 0.1% of the total volume of the published information flow 40% of which is formed by information noise.
conduct a literature review. Then we introduce the data set and the method HDCCA with its realization steps. In the next part, we construct the hybrid documents co-citation network, and apply both cluster analysis and network analysis to uncover the
We investigated how cluster analysis and diversity-ordering can be used for the classification of geographically and historically distinct plant and insect communities. The study sites include fens and Brachypodium pinnatum dominated grasslands. The stands of the fen vegetation type could be arranged into similar groups by cluster analysis, principal component analysis and diversity ordering techniques. In the case of the B. pinnatum dominated grasslands of diverse development, however, no groups could be differentiated on the basis of either diversity ordering or ordination. Of the various cluster analyses, the result of global optimisation was similar to those of PCA ordination and diversity ordering techniques.
Abstract
Objective This paper aimed to examine the reliability of co-citation clustering analysis in representing the research history of subject by comparing the results from co-citation clustering analysis with a review written by authorities. Methods Firstly, the treatment of traumatic spinal cord injury was chosen as an investigated subject to be retrieved the resource articles and their references were downloaded from Science Citation Index CD-ROM between 1992 and 2002. Then, the highly cited papers were arranged chronologically and clustered with the method of co-citation clustering. After mapping the time line visualization, the history and structure of treatment of spinal cord injury were presented clearly. At last, the results and the review were compared according the time period, and then the recall and the precision were calculated. Results The recall was 37.5%, and the precision was 54.5%. The research history of traumatic spinal cord injury treatment analyzed by co-citation clustering was nearly consistent with authoritative review, although some clusters had shorter period than which was summarized by professionals. Conclusion This paper concluded that co-citation clustering analysis was a useful method in representing the research history of subject, especially for the information researchers, who do not have enough professional knowledge. Its demerit of low recall could be offset by combination this method with other analytic techniques.
International competitiveness is influenced by globalization processes in the world economy. This process changes the comparative advantages of each country and thus the shares of individual countries in world trade. BRICS countries have quickly strengthened their influence in international trade, and thus the European Union must face new pressure in competitiveness from their side. The aim of this paper is to define key factors of foreign trade competitiveness by an application of factor analysis and identify countries with similar characteristics of competitiveness factors by an application of cluster analysis. Factor and cluster analysis contain indicators of foreign trade which describe the driving forces of competitiveness, also in terms of long-term potentiality, and those which are direct or indirect outcomes of a competitive society and economy. Based on the results of the factor analysis, it is possible to classify the evaluated territories according to the level of foreign trade advancement by cluster analysis.
COVID-19 crisis. The study includes 24 EU economies. The methodology is based on multidimensional cluster analysis based on the following six input variables in the year 2021: share of renewables and biofuels in the total energy consumption; 1 weight of
