A Kind of Music Retrieval Model Based on Nested Sparse Matrix in P2P Network
Year: 2012
Type: article
Abstract: In view of existing situation that large collections of music data are shared by numerous users in Peer-to-Peer network, people raise higher demands for content-based music information retrieval. For more efficient searching, this paper mainly involves the following three points: Firstly, filter out the repeating patterns in original piece of music and extract the key information, which can reduce the space occupied by index structure. Secondly, we propose a music index structure based on ordered orthogonal list to store music features in a nested sparse matrix. Finally, a related search table is proposed according to user’s search history to store the global connectivity of the network. Experimental results show that the proposed model can reduce the traffic cost and average response time effectively and have high retrieval accuracy.
Source: Advanced materials research
Authors: Xian Fu Meng, Chun Li
Institution: Dalian University of Technology
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2032455516