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Component study of co-word analysis.

机译:共词分析的成分研究。

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Co-word analysis is a technique proposed to detect the intellectual structure of science by clustering words from scientific literature. It counts the co-occurrence of term pairs in texts, computes the association between terms using special indexes, and clusters terms into various graphical structures. Each graph (map) represents a theme in a research field and the graphs from several continuous periods can map the dynamics of the research field.; This research includes a series of systematic component comparison studies on the co-word analysis technique. On the one hand, a set of co-word analysis tests are conducted using two different strength indexes to compute the association between terms. The indexes being tested include: (i) the inclusion index (I); and, (ii) the equivalence index (E). On the other hand, a set of co-word analysis tests are carried out using different input term units. The input term sets being tested include: (i) terms from the subject heading field of articles (thesaurus terms); (ii) terms from article titles; All the tests are conducted on the same test collection drawn from the INSPEC database and use the same two-pass clustering procedure. Only one of the other components is changed in order to identify the effects of that component on the final results from the test. Outputs of all the tests are evaluated by human experts on some pre-selected criteria (correctness of linkage, specificity level, completeness, centrality, density). Statistical analyses are conducted to determine if the component being tested affects the results of co-word analysis significantly and how they affect the results.; The results of human evaluation and statistical analyses show that both the strength index component and input term component affect the output from co-word analysis in significant ways. The resulting maps from the inclusion index test are much more general than those from the equivalence index. The test with title terms gives the most specific maps while the test with title
机译:共词分析是一种通过对科学文献中的单词进行聚类来检测科学知识结构的技术。它计算文本中术语对的同时出现,使用特殊索引计算术语之间的关联,并将术语聚类为各种图形结构。每个图(图)代表研究领域中的主题,并且连续几个时期的图可以映射研究领域的动态。这项研究包括对共词分析技术的一系列系统组件比较研究。一方面,使用两个不同的强度指标进行了一组共词分析测试,以计算术语之间的关联。被测试的指标包括:(i)包含指数(I); (ii)等效指数(E)。另一方面,使用不同的输入术语单位进行了一组共词分析测试。被测试的输入术语集包括:(i)文章主题标题域中的术语(同义词库术语); (ii)文章标题中的术语;所有测试均在从INSPEC数据库提取的同一测试集合上进行,并使用相同的两次通过聚类过程。为了确定该组件对测试最终结果的影响,仅更改了其他组件之一。人类专家根据某些预先选择的标准(链接的正确性,特异性水平,完整性,中心性,密度)对所有测试的输出进行评估。进行统计分析,以确定所测试的组件是否显着影响共词分析的结果以及它们如何影响结果。人工评估和统计分析的结果表明,强度指数成分和输入术语成分都在很大程度上影响共词分析的输出。包含指数测试得出的映射比等效索引生成的映射要普遍得多。带有标题词的测试提供最具体的地图,而带有标题词的测试

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