Visualization of Corpus Data by a Dual Hierarchical Data Visualization Technique
Source: Ochanomizu University
The paper presents a technique for visualization of corpus data consists of thousands of Japanese newspaper articles, and introduces several interesting trends discovered from the results. The technique first generates keyword-document matrices from the newspaper corpus, and respectively applies hierarchical clustering for rows and columns of the matrices. It then displays the two sets of clusters applying the own dual hierarchical data visualization technique. The visualization technique provides a mechanism to interact the two visualization components each other, so that users can freely explore the detail of the corpus data. This paper first describes the algorithm of the dual hierarchical data visualization technique, and then introduces the implementation and experiments of the visualization of the newspaper corpus data.