An Automatic Graph Generation Method For Scholarly Papers Based On Table Structure Analysis

For papers reporting on experiments, the types of experiinent performed are important, as are the results they generate. Tables are frequently used to show experimental results and are suited to understanding accurate numerical values. However, they are not suited to visually comparing or observing changes in many values at once. In this paper, we propose an automatic graph-generation method for data presented in tabular form. We first convert PDF files of scholarly papers into XML files to analyze the structure of their tables. We then generate graphs based on this table-structure analysis. We also examine the types of graphs that are easy to understand visually.