Recommendation research based on general content probabilistic latent semantic analysis model
ZHANG Wei1,HUANG Wei2,XIA Limin1
1. School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China
2. Department of Computer Engineering, Changsha Aeronautical Vocational and Technical College, Changsha Hunan 410124, China
Abstract：In the recommendation system, some new items and the accuracy issue cannot be well controlled. Therefore, a new recommendation method based on general content Probabilitistic Latent Semantic Analysis (PLSA) model was proposed. The general content PLSA model contained two latent variables indicating the user groups and item groups, and contained features of items that were trained by asymmetric learning algorithm. The experimental results show that the new method has good quality for recommendation on three different data sets.
2013, Vol. 33 
