Recommender system using sentiment analysis
Vidya Adekar, Nitin Borkar, Sonali Acharya, Prathamesh Kedar · International journal of advance research and innovative ideas in education · 2018
Recommender systems are meant for recommending products to customers according to their interests. Recommender system has several features namely, data collection and processing, recommender model, recommendation post processing and user interface etc. in order to recommend proper products to given user. These recommendations systems rely on one or more recommendation techniques. The paper proposes a recommender system that will recommend the products that are relevant to user's interests in different fields/ areas/ domains. User interests are extracted with the help of his/her activities in social networking sites such as Facebook. Generally, recommender systems are recommended the products or services regarding one specific domain whereas the proposed system is able to recommend the products from various domains. Along with that, system can recommend text articles as well that user might find on his/her interests.