Detection of Difference between News Articles on the Same Topic Based on Sequential Comparison

Currently, a lot of news articles are published on theWeb, and it is getting easier for us to read them. However, the number of articles are too large for us to read all of them. Although some Web sites cluster/classify news articles into some topics (categories), it is not enough since a large number of articles are still in each topic. Detecting difference between articles on one topic will be one of the solution to comprehend the whole topic. In this paper, we propose a method for detection of difference between news articles on the same topic. Articles are sequentially compared by three different comparison units: paragraphs, sentences, and simple sentences. Our method is evaluated by applying it to Japanese news articles.