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題名 Mining polyphonic repeating patterns from music data using bit-string based approaches
作者 Shan, Man-kwan;Chiu, Shih-Chuan;Huang, Jiun-Long;Li, Hua-Fu
沈錳坤
貢獻者 資科系
日期 2009
上傳時間 17-六月-2015 16:22:14 (UTC+8)
摘要 Mining repeating patterns from music data is one of the most interesting issues of multimedia data mining. However, less work are proposed for mining polyphonic repeating patterns. Hence, two efficient algorithms, A-PRPD (Apriori-based Polyphonic Repeating Pattern Discovery) and T-PRPD (Tree-based Polyphonic Repeating Pattern Discovery), are proposed to discover polyphonic repeating patterns from music data. Furthermore, a bit-string method is developed for improving the efficiency of the proposed algorithms. Experimental results show that the proposed algorithms, A-PRPD and T-PRPD, are both effective and efficient methods for mining polyphonic repeating patterns from synthetic music data and real data.
關聯 International Conference on Multimedia Computing and Systems/International Conference on Multimedia and Expo - ICME(ICMCS) , pp. 1170-1173
資料類型 article
DOI http://dx.doi.org/10.1109/ICME.2009.5202708
dc.contributor 資科系
dc.creator (作者) Shan, Man-kwan;Chiu, Shih-Chuan;Huang, Jiun-Long;Li, Hua-Fu
dc.creator (作者) 沈錳坤zh_TW
dc.date (日期) 2009
dc.date.accessioned 17-六月-2015 16:22:14 (UTC+8)-
dc.date.available 17-六月-2015 16:22:14 (UTC+8)-
dc.date.issued (上傳時間) 17-六月-2015 16:22:14 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75900-
dc.description.abstract (摘要) Mining repeating patterns from music data is one of the most interesting issues of multimedia data mining. However, less work are proposed for mining polyphonic repeating patterns. Hence, two efficient algorithms, A-PRPD (Apriori-based Polyphonic Repeating Pattern Discovery) and T-PRPD (Tree-based Polyphonic Repeating Pattern Discovery), are proposed to discover polyphonic repeating patterns from music data. Furthermore, a bit-string method is developed for improving the efficiency of the proposed algorithms. Experimental results show that the proposed algorithms, A-PRPD and T-PRPD, are both effective and efficient methods for mining polyphonic repeating patterns from synthetic music data and real data.
dc.format.extent 130 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) International Conference on Multimedia Computing and Systems/International Conference on Multimedia and Expo - ICME(ICMCS) , pp. 1170-1173
dc.title (題名) Mining polyphonic repeating patterns from music data using bit-string based approaches
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1109/ICME.2009.5202708
dc.doi.uri (DOI) http://dx.doi.org/10.1109/ICME.2009.5202708