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Impovement of a Label Extraction Method for a Risk Search System

Authors: Shigeaki Sakurai, Ryohei Orihara


This paper proposes an improvement method of classification efficiency in a classification model. The model is used in a risk search system and extracts specific labels from articles posted at bulletin board sites. The system can analyze the important discussions composed of the articles. The improvement method introduces ensemble learning methods that use multiple classification models. Also, it introduces expressions related to the specific labels into generation of word vectors. The paper applies the improvement method to articles collected from three bulletin board sites selected by users and verifies the effectiveness of the improvement method.

Keywords: Text Mining, Ensemble Learning, Corporate Reputation, Risk search system, Bulletin board site

Digital Object Identifier (DOI):

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