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Analysis and Indexing—indexing methods

By Rui Cai, Chao Zhang, Lei Zhang and Wei-ying Ma


The growth of music resources on personal devices and Internet radio has increased the need for music recommendations. In this paper, aiming at providing an efficient and general solution, we present a search-based solution for scalable music recommendations. In this solution a music piece is first transformed to a music signature sequence in which each signature characterizes the timbre of a local music clip. Based on such signatures, a scale-sensitive method is then proposed to index the music pieces for similarity search, using the locality sensitive hashing (LSH). The scale-sensitive method can numerically find the appropriate parameters for indexing various scales of music collections, and thus can guarantee a proper number of nearest neighbors are found in search. In the recommendation stage, representative signatures from snippets of a seed piece are extracted as query terms, to retrieve pieces with similar melodies for suggestions. We also design a relevance-ranking function to sort the search results, based on the criteria that include matching ratio, temporal order, term weight, andmatching confidence. Finally, with the search results, we propose a strategy to generate a dynamic playlist which can automatically expand with time. Evaluations of several music collections at various scales showed that our approach achieves encouraging results in terms of recommendation satisfaction and system scalability

Topics: Categories and Subject Descriptors H.5.5 [Information Interfaces and Presentation, Sound and Music Computing—methodologies and techniques, systems, H.3.3 [Information Storage and Retrieval, Information Search and Retrieval—retrieval models, search process
Year: 2011
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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