Deep Auto-Encoder によるイベント記事の分析

抄録

In the text mining, it must be conducted a preprocessing in order to obtain a structured data representation from the raw text unstructured. Preprocessing of the raw data greatly affect the results and accuracy of the mining process. In this paper, we extract text feature amount by using the Deep Auto-Encoder which is a kind of Deep Learning. (It's also called ``Semantic Hashing'') The data used in this article is the actual event information that is delivered by ``びもーる''. It was found that the features extracted by Deep Auto-Encoder from the real event information articles is useful for classification of event information.