关键词: 音乐推荐系统, 分形维, 特征抽取, 向量相似度

Abstract: Music recommendation system is to provide needful music for users from the candidate music library based on analyzing the user’s browsing history data.The classification of whole database according to music style is the key point of this system.Then this paper proposes a novel music feature for achieving music classification.Firstly the regular data sets of music feature are constructed.Then the attribute of data sets is reduced based on fractal dimension theory and the recommendation features are obtained for each music.Also a new distance measure is given for the similarity of this recommendation feature.During the experiment based on database including six styles of music，simulation results demonstrate the effectiveness of the proposed music recommendation feature and the new distance.Compared with the study of current content-based music retrieval，music recommendation feature can greatly reduce the requirement of database memory and provide a promising application for the network exploitation of music recommendation system.

Key words: music recommendation system, fractal dimension, feature extraction, vector similarity