A Kind of Music Retrieval Model Based on Nested Sparse Matrix in P2P Network

摘要: In view of existing situation that large collections music data are shared by numerous users in Peer-to-Peer network, people raise higher demands for content-based information retrieval. For more efficient searching, this paper mainly involves the following three points: Firstly, filter out repeating patterns original piece and extract key information, which can reduce space occupied index structure. Secondly, we propose a structure based on ordered orthogonal list to store features nested sparse matrix. Finally, related search table is proposed according user’s history global connectivity network. Experimental results show model traffic cost average response time effectively have high retrieval accuracy.