This paper brings forward a method of auto-construction of concept map based on term co-occurrence technique. Firstly,the paper selects the terms and computes the relation strength between terms to form the proximity matrix.
提出了一种利用词共现技术自动构建概念图的方法,首先进行词条选择,并计算词条之间的关联强度生成关系矩阵;接着,从关系矩阵中挖掘概念图;最后,利用可视化技术动态展示概念图。
参考来源 - 基于词共现的概念图自动构建研究·2,447,543篇论文数据，部分数据来源于NoteExpress
It is explained that the term co-occurrence graph of text is highly clustered and has short path length, which proves that texts have small world structure.
为此首先证明由文本形成的词汇共现图呈现短路径，高聚集度的特性，说明小世界结构存在于文本中；
In this paper, we use the co-occurrence path to explain the relationship between the index words and extract the semantic information in the term-term matrix to expand the query.
本文首先利用传递度来量化索引词与索引词间的关联关系，然后利用索引词与索引词的关系矩阵中存在的语义关系对查询向量进行智能扩展。
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