Authors : P. Pabitha, G. Amirthavalli and M. Rajaram
Abstract: Recommendation systems refines enormous amount of data and provides suggestions on items or ratings of items which is appealing to the user. Although, the recommender systems depends on content based approach or collaborative filtering technique to make recommendations, these methods suffers from cold start and data sparsity problem. To overcome the limitations of the aforementioned problems, a weight based approach is proposed for better performance. The main criterion for building a recommender system is to exploit useful content and provide better recommendations with minimal processing time. The proposed system is a web based client side application which uses user profiles to form neighbourhood and calculates ratings using weights. For newcomers a profile is constructed based on past history and current preference. The resources which might be of interest to the user are predicted from calculated ratings.
P. Pabitha, G. Amirthavalli and M. Rajaram, 2015. Weight Based Approach for Resource Recommendation. International Journal of Soft Computing, 10: 83-86.