摘要
为了让用户根据歌词内容快速精准地检索音乐,提出一种基于word2vec的中文歌词关键词提取算法.算法运用word2vec将歌词表征为词向量,根据词向量计算词语之间的相似度,其次通过K-means聚类算法得到歌词关键词.同时与基于TFIDF、LDA模型的歌词关键词提取结果进行比较,发现从该算法得出的10个关键词中抽取与人工标注相同的2-5个时,准确率明显增加.
In order to make users search music by lyrics rapidly and accurately,A Chinese lyrics’ keyword extraction algorithm based on word2 vec is proposed,which is a model for deep learning.Firstly,this algorithm characterizes lyrics as word vector by word2 vec.Secondly,it calculates the similarity between words and words.Then we can get keywords by K-means algorithm.At the same time,this algorithm is better than TFIDF and LDA when 2-5 of 10 keywords,which is found in manual work.
作者
蒙晓燕
殷雁君
MENG Xiao-yan;YIN Yan-jun(College of Computer, Inner Mongolia Normal University, Hohhot 010022,China)
出处
《内蒙古师范大学学报(自然科学汉文版)》
CAS
2018年第2期137-140,共4页
Journal of Inner Mongolia Normal University(Natural Science Edition)
基金
内蒙古自治区高等学校科学研究项目基金资助(NJZY13047)