Impovement of a Label Extraction Method for a Risk Search System
نویسندگان
چکیده
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, Risk search system, Corporate reputation, Bulletin board site, Ensemble learning
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