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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

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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.

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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.

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, scholars usually cluster analysis, multidimensional scaling analysis and factor analysis to conduct co-citation analysis. Compared to the scholars’ traditional qualitative analysis (including individual induction, interviews and other subjective methods

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statistical significant difference between the two classes of diseases in the proportions of missing papers. For each year, a Kruskal–Wallis rank sum test yielded a non-significant result [χ 2 (1) < 1.5, P > 0.05]. Cluster analysis

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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

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Fig. 4 Dendrogram of the authors in 11-Slice Twelve groups are forming according to the cluster analysis from bottom to top. Group 1, group 3, group 4, group7, group 8 all come from

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grouped and considered as single keywords. Another innovative method was “word cluster analysis”, combining and analyzing “words in title”, “author keywords”, and “KeyWords Plus”. This was used to discover the research trend, or “research hotspots

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more centrally. Eigenvector centrality determines a journal's overall centrality in the network (Bonacich 1972 ). Another indicator of the structure of the citation pattern is how journals cluster. Cluster analysis identifies groups within data

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Abstract

The information analysis process includes a cluster analysis or classification step associated with an expert validation of the results. In this paper, we propose new measures of Recall/Precision for estimating the quality of cluster analysis. These measures derive both from the Galois lattice theory and from the Information Retrieval (IR) domain. As opposed to classical measures of inertia, they present the main advantages to be both independent of the classification method and of the difference between the intrinsic dimension of the data and those of the clusters. We present two experiments on the basis of the MultiSOM model, which is an extension of Kohonen's SOM model, as a cluster analysis method. Our first experiment on patent data shows how our measures can be used to compare viewpoint-oriented classification methods, such as MultiSOM, with global cluster analysis method, such as WebSOM. Our second experiment, which takes part in the EICSTES EEC project, is an original Webometrics experiment that combines content and links classification starting from a large non-homogeneous set of web pages. This experiment highlights the fact that break-even points between our different measures of Recall/Precision can be used to determine an optimal number of clusters for web data classification. The content of the clusters obtained when using different break-even points are compared for determining the quality of the resulting maps.

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