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On-Device Gender Prediction Framework Based on the Development of Discriminative Word and Emoticon Sets
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 Title & Authors
On-Device Gender Prediction Framework Based on the Development of Discriminative Word and Emoticon Sets
Kim, Solee; Choi, Yerim; Kim, Yoonjung; Park, Kyuyon; Park, Jonghun;
User demographic information is necessary in order to improve the quality of personalized services such as recommendation systems. Mobile data, especially text data, is known to be effective for prediction of user demographic information. However, mobile text data has privacy issues so that its utilization is limited. In this regard, we introduce an on-device gender prediction framework utilizing mobile text data while minimizing the privacy issue. Discriminative word and emoticon sets of each gender are constructed from web documents written by authors of each gender. After gender prediction is performed by comparing discriminative word and emoticon sets with a user's mobile text data, an ensemble method that combines two prediction results draws a final result. From experiments conducted on real-world mobile text data, the proposed on-device framework shows promising results for gender prediction.
gender prediction;text data;ensemble method;mobile user;on-device prediction;
 Cited by
모바일 사용자의 성별 예측을 위한 식별 및 인기 단어 집합 기반 2단계 기기 내 분석,최예림;박규연;김소이;박종헌;

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