Loading [a11y]/accessibility-menu.js
Mining polyphonic repeating patterns from music data using bit-string based approaches | IEEE Conference Publication | IEEE Xplore

Mining polyphonic repeating patterns from music data using bit-string based approaches


Abstract:

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...Show More

Abstract:

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.
Date of Conference: 28 June 2009 - 03 July 2009
Date Added to IEEE Xplore: 18 August 2009
Print ISBN:978-1-4244-4290-4

ISSN Information:

Conference Location: New York, NY, USA

References

References is not available for this document.