2017 年 12 巻 2 号 p. 329-334
This study aims to compress web news, delivered as a big-data source after disasters. In this paper, article clustering, which is a combination of conventional means and an algorithm that selects the representative articles of each cluster, is designed and adopted. Experiments are conducted by evaluators. The proposed algorithm is in accord with the evaluators for 50% of the clustering and for about 30% to 40% of the representative-article selection.
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