TV Audience Classification Model Based on Transfer Learning
In response to the problem that smart TV cannot obtain TV audience feature data,which makes it difficult to accurately classify viewers,this article proposes a TV audience classification model based on transfer learning. Firstly,analyze the characteristics of users and their preferred TV programs,and train a base model,then,using real TV audience data and their favorite TV programs,transfer the base type to the TV audience classification task. Experimental results have shown that the proposed model has good classification accuracy.
TV audience classificationtransfer learningdeep neural networks
NETL
NSTL
万方数据
