標題: | Online mining maximal frequent structures in continuous landmark melody streams |
作者: | Li, HF Lee, SY Shan, MK 資訊工程學系 Department of Computer Science |
關鍵字: | machine learning;data mining;landmark melody stream;maximal melody structure;Online algorithm |
公開日期: | 1-Aug-2005 |
摘要: | In this paper, we address the problem of online mining maximal frequent structures (Type I & II melody structures) in unbounded, continuous landmark melody streams. An efficient algorithm, called MMSLMS (Maximal Melody Structures of Landmark Melody Streams), is developed for online incremental mining of maximal frequent melody substructures in one scan of the continuous melody streams. In MMSLMS, a space-efficient scheme, called CMB (Chord-set Memory Border), is proposed to constrain the upper-bound of space requirement of maximal frequent melody structures in such a streaming environment. Theoretical analysis and experimental study show that our algorithm is efficient and scalable for mining the set of all maximal melody structures in a landmark melody stream. (c) 2005 Elsevier B.V. All rights reserved. |
URI: | http://dx.doi.org/10.1016/j.patrec.2005.01.016 http://hdl.handle.net/11536/13438 |
ISSN: | 0167-8655 |
DOI: | 10.1016/j.patrec.2005.01.016 |
期刊: | PATTERN RECOGNITION LETTERS |
Volume: | 26 |
Issue: | 11 |
起始頁: | 1658 |
結束頁: | 1674 |
Appears in Collections: | Articles |
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