Extraction of Statistical Terms and Co-occurrence Networks from Newspapers
Haruka Saito, Hideki Derek Kawai, Masaaki Tsuchida, Hiroyuki Mizuguchi, Dai Kusui · 2007
In this paper, we automatically extract statistical terms and build their co-occurrence networks from newspapers. Statistical terms are expression of the measurements of statistics to watch the movements of phenomena; birth rates, public approval rating of the Cabinet and so on. In recent years, we have a vast amount of available information because of computer-ization and the technologies of making their overview and enhancement of their values are noticed. One of them is the technology of visualizing information of so-cial trend and movements from newspapers. For visu-alizing trend information, there some approaches. In this paper, we take the approach of building networks of causal relations among the statistical terms. To ex-tract statistical terms, we propose extraction method using suffixes. To extract causal relations among sta-tistical terms, we first extract co-occurrence relations and next show them with the networks. We can ex-tract many statistical terms with high accuracy by our method and find interesting links among some statisti-cal terms by our co-occurrence networks. 1