Hypothesis generation guided by co-word clustering
Hypothesis generation guided by co-word clustering
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DOI：
10.1023/a:1021954808804
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发表时间：
2004
期刊：
影响因子：
3.9
通讯作者：
J. Stegmann;G. Grohmann
中科院分区：
文献类型：
--
作者：
J. Stegmann;G. Grohmann
共词分析应用于包含在互补但不相交的文献集合中的MEDLINE文档分配的关键词。在不相交文献的策略图中，基于包含关键字的聚类的内部密度和外部中心性，在中心性和密度低于中位数的区域发现了中间项（连接不相交的伙伴）。在中间文献的策略图中，可以发现表示不相交的文献主题的术语非常接近。基于中心性-密度比，发现特征值可以快速识别包含可能的中间和不相交伙伴项的群集。将该方法应用于已研究的不接合对雷诺病-鱼油，偏头痛-镁，容易检测到已知和未知（但相关的）中间和不接合的伴侣项。将该方法应用于朊病毒的文献中，发现锰可能是不接合的伴侣项。结果表明，共词聚类是一种有效的基于文献的假设生成和知识发现方法。
Co-word analysis was applied to keywords assigned to MEDLINE documents contained in sets of complementary but disjoint literatures. In strategical diagrams of disjoint literatures, based on internal density and external centrality of keyword-containing clusters, intermediate terms (linking the disjoint partners) were found in regions of below-median centrality and density. Terms representing the disjoint literature themes were found in close vicinity in strategical diagrams of intermediate literatures. Based on centrality-density ratios, characteristic values were found which allow a rapid identification of clusters containing possible intermediate and disjoint partner terms. Applied to the already investigated disjoint pairs Raynaud"s Disease - Fish Oil, Migraine - Magnesium, the method readily detected known and unknown (but relevant) intermediate and disjoint partner terms. Application of the method to the literature on Prions led to Manganese as possible disjoint partner term. It is concluded that co-word clustering is a powerful method for literature-based hypothesis generation and knowledge discovery.