Improving the co-word analysis method based on semantic distance
Jia Feng• Yun Qiu Zhan1• Hao Zhang
Received: 24 July 2016
 Akade´miai Kiado´ , Budapest, Hungary 2017

Abstract： We propose an improvement over the co-word analysis method based on semantic distance. This combines semantic distance measurements with concept matrices generated from ontologically based concept mapping. Our study suggests that the co-word analysis method based on semantic distance produces a preferable research situation in terms of matrix dimensions and clustering results. Despite this method’s displayed advantages, it has two limitations: first, it is highly dependent on domain ontology; second, its efficiency and accuracy during the concept mapping progress merit further study. Our method optimizes co-word matrix conditions in two aspects. First, by applying concept mapping within the labels of the co-word matrix, it combines words at the concept level to reduce matrix dimensions and create a concept matrix that contains more content. Second, it integrates the logical relationships and concept connotations among studied concepts into a co-word matrix and calculates the semantic distance between concepts based on domain ontology to create the semantic matrix.

本文提出了一种基于语义距离的共词分析方法改进方法。本文把语义距离测度和基于概念地图生成的概念矩阵综合在一起。该研究表明，根据矩阵维度和聚类结果的基于语义距离的共词分析方法产生了一个较为理想的结果。这种方法有一定的优势，但也有两个方面的局限。首先，它高度依赖于领域本体，其次，在概念地图形成的有效性和准确性还有待进一步研究。这种方法在两个方面优化了共词矩阵。首先，把概念地图应用到共词矩阵的标签中，它把词在概念水平进行了结合，降低了矩阵的维度，而且生成了一个包含更多内容的概念矩阵。其次，它把逻辑关系的概念的内容有机整合之后形成一个共词矩阵，通过基于领域本体计算概念间的距离，然后生成语义矩阵。

Keywords: Co-word analysis  Semantic distance  Concept mapping  Semantic matrices

Improving the co-word analysis method based on semantic distance.pdf