Users Ranking Pattern Based Trust Model Regularization in Product Recommendation
U.B. Sneha · International Journal for Research in Applied Science and Engineering Technology · 2018
Recommendation system is used to recommend resources that user may be interested in by mining user interests and preferences. The system provides users personalized assistances and information about products or services of interest to support their decision-making processes. Personalization deals with adapting to the individual requirements, interests and preferences of each user. The main concepts of the Product recommendation is recommending the product items based on user trust, rating and review score. Trust is a measure that indicates the usefulness service of products. It reduces the data sparsity problems and cold start problems and their degradation of recommendation performance. The proposed system provides the product recommendation based on frequent pattern mining algorithm for eliminate the false rating and similarly provide the better recommendation accuracy to users. In addition to Linguistic dissimilarity problems will be overcome by using Natural Language Processing for build the better review score.