南京信息工程大学学报2019，Vol.11Issue(1)：68-76,9.DOI:10.13878/j.cnki.jnuist.2019.01.013
基于多模态的音乐推荐系统
A music recommendation system based on multi-modal fusion
摘要
Abstract
Despite the continuous enrichment of music, the underlying music features are often overlooked when using traditional collaborative filtering.By multi-modal fusion of audio features and lyric information and supplementing the fusion information feature as a collaborative filtering recommendation, a multi-modal music recommendation system is proposed.This studyprimarily discusses the extraction of audio features and lyrics information and uses the LDA topic model to reduce the character dimension of the lyrics information. For the multi-model fusion problem, this study proposes an EFFC fusion method, and compares the results of multi-modal fusion with the results using single-mode.For result recommendations, the user interest model is established based on the multi-modal information feature with the input of LSTM networks to filter and optimize the user group.The results show that the multi-modal music recommendation system reduces the SSE of the result from 2. 009 to 0. 388 6, verifying the effectiveness of the method.关键词
音乐推荐/协同过滤/LDA主题模型/多模态融合/LSTM神经网络Key words
music recommendation/collaborative filtering/LDA topic model/multi-modal fusion/LSTM networks分类
信息技术与安全科学引用本文复制引用
龚志,邵曦..基于多模态的音乐推荐系统[J].南京信息工程大学学报,2019,11(1):68-76,9.基金项目
国家自然科学基金 (70573025) （70573025）
