技术竞争对手的视觉群体识别方法采用LinLog图聚类算法

Hongqi Han, X. An, Donghua Zhu, Xuefeng Wang
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引用次数: 0

摘要

可视化技术是科技情报分析专家识别技术竞争对手群体的有力手段。常见的可视化方法倾向于创建符合美学标准的图形,而不是寻找更好的聚类,并且它们的分析结果可能提供误导性信息。提出了一种基于LinLog图聚类算法的技术群体识别过程模型,以寻找更好的竞争对手群体。在模型中,每对竞争对手的技术相似值是根据它们在子领域的研发产出来衡量的,当两个竞争对手的相似值高时,它们之间存在联系;采用LinLog算法,以竞争对手为节点,以竞争对手的链接为边,以技术相似度为边的权值,以生成更好的聚类。实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual group identification method of technical competitors using LinLog graph clustering algorithm
Visualization technique is a powerful method used by science and technology intelligence analysis experts to identify technical competitor groups. Common visualization methods tend to create graphs meeting the aesthetic criteria instead of finding better clusters, and their analysis results may provide misleading information. A process model of technical group identification method was presented using LinLog graph clustering algorithm to find better competitor groups. In the model, technical similarity value of each pair of competitors is measured based on their R&D output in sub-fields, and two competitors have a link when they have high similarity value; LinLog algorithm, which is aimed at producing better clusters, was employed to layout graph with competitors as nodes, their links as edges and technology similarity values as weights of edges. Experiment results show the efficiency of presented method.
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