Sophisticated Text Mining System for Extracting and Visualizing Numerical and Named Entity Information from a Large Number of Documents

We have developed a system that can semiautomatically extract numerical and named entity sets from a large number of Japanese documents and can create various kinds of tables and graphs. In our experiments, our system semiautomatically created approximately 300 kinds of graphs and tables at precisions of 0.2–0.8 with only 2 h of manual preparation from a 2-year stack of newspapers articles. Note that these newspaper articles contained a large quantity of data, and all of them could not be read or checked manually in such a short amount of time. From this perspective, we concluded that our system is useful and convenient for extracting information from a large number of documents. We have constructed a demonstration system. In this paper, we briefly describe the demonstration system.