https://scholars.lib.ntu.edu.tw/handle/123456789/632436
標題: | Gender identification and age estimation of users based on music metadata | 作者: | Wu M.-J JYH-SHING JANG Lu C.-H. |
公開日期: | 2014 | 起(迄)頁: | 555-560 | 來源出版物: | Proceedings of the 15th International Society for Music Information Retrieval Conference, ISMIR 2014 | 摘要: | Music recommendation is a crucial task in the field of music information retrieval. However, users frequently withhold their real-world identity, which creates a negative impact on music recommendation. Thus, the proposed method recognizes users’ real-world identities based on music metadata. The approach is based on using the tracks most frequently listened to by a user to predict their gender and age. Experimental results showed that the approach achieved an accuracy of 78.87% for gender identification and a mean absolute error of 3.69 years for the age estimation of 48403 users, demonstrating its effectiveness and feasibility, and paving the way for improving music recommendation based on such personal information. © Ming-Ju Wu, Jyh-Shing Roger Jang, Chun-Hung Lu. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057947447&partnerID=40&md5=bdd1f8f1735ad6095a347687d6a433b2 https://scholars.lib.ntu.edu.tw/handle/123456789/632436 |
SDG/關鍵字: | Information retrieval; Age estimation; Gender identification; Mean absolute error; Music information retrieval; Music recommendation; Personal information; Real-world; Metadata |
顯示於: | 資訊工程學系 |
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