LAUSR

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.