  Today, Internet is one of the widest available media worldwide.
Recommendation systems are increasingly being used in various applications such
as movie recommendation, mobile recommendation, article recommendation and etc.
Collaborative Filtering (CF) and Content-Based (CB) are Well-known techniques
for building recommendation systems. Topic modeling based on LDA, is a powerful
technique for semantic mining and perform topic extraction. In the past few
years, many articles have been published based on LDA technique for building
recommendation systems. In this paper, we present taxonomy of recommendation
systems and applications based on LDA. In addition, we utilize LDA and Gibbs
sampling algorithms to evaluate ISWC and WWW conference publications in
computer science. Our study suggest that the recommendation systems based on
LDA could be effective in building smart recommendation system in online
communities.
