Proposed Model for Emotions Based Recommender Systems Using Reviews - Uppal, Veepu; Singh, Rajesh Kumar (International Journal of Computer Sciences and Engineering, 2019)
Information Analysis and extraction is difficult due to huge amount of data on the Internet. Recommender Systems provide efficient and useful information for user according to their preferences. Large numbers of research have been accomplished on Emotion based Recommender systems Techniques. These techniques extract the human emotions for any items from reviews. In this paper we summarize the existing techniques to extract emotions from reviews written by users for different items and propose a new method to design a dynamic search engine which will extract the online reviews and recommend items of different category on the basis of user search. Further our proposed technique will recommend items to user by combination of online reviews and ratings of product too. The spam reviews will be identified and removed.