Research on the Application of Improved LDA Model in Film and Television Works Recommendation
In order to solve the accuracy problem of film and television resources recommendation,the latent Dirichlet allocation(LDA)is introduced to complete the analysis of film and television works review data.Considering that LDA can not reflect the importance of each feature word,the attention mechanism is embedded into the network to improve model accuracy.The re-sults show that in the recommendation accuracy test,by the MovieLens-1M data,the proposed model has an accuracy of 0.936,which is the best compared to similar technologies in terms of accuracy.From this,it can be seen that the proposed rec-ommendation model has excellent application results in system stability and recommendation effectiveness.
recommendation algorithmfilm and television workLDAattention mechanism
万方数据
维普
