Review based Feature Matrix for Predicting ratings in Recommender System
Prafulla Bharat Bafna, Shailaja C. Shirwaikar, Dhanya Pramod, Anagha Vaidya · International Journal of Engineering and Technology · 2017
Recommender systems are acquiring extensive popularity and have become essential component of on-line business handling tools because of their capability of providing personalized guidance in selecting products and services.Collaborative Filtering that brings in the popularity aspect of the item amongst the user base, heavily depends on the ratings provided by the users, while Contentbased Filtering that brings out the item's features matching the user's taste, requires content information as also user's preference information.Service providers usually invite users to share their experience about the use of service in the form of reviews and ratings.Reviews which are verbose contain a rich source of information about the service's features as also user's preferences while ratings are usually sparse due to user's reluctance to quantify.A feature matrix generated by processing review information using semantic similarity based on synsets can be used along with sparse ratings to generate the complete predicted ratings matrix.The paper presents a modified matrix factorization approach for recommendations using the review based feature matrix Keyword-Recommender system, synsets, predictive model.