A Collaborative Approach for Web Personalized Recommendation System
- Nirav M. Khetra
- Shruti B. Yagnik
Recommendation, Typicality, Collaborative Filtering
Collaborative filtering (CF) is an important and popular technology for recommender systems. However, current CF methods suffer from such problems as data sparsity, recommendation inaccuracy and big-error in predictions. A distinct feature of typicality-based CF is that it finds ‘neighbours’ of users based on user typicality degrees in user groups (instead of the co-rated items of users, or common users of items, as in traditional CF). To the best of our knowledge, there has been no prior work on investigating CF recommendation by combining object typicality. Further, it can obtain more accurate predictions with less number of big-error predictions.
Nirav M. Khetra, Shruti B. Yagnik. "A Collaborative Approach for Web Personalized Recommendation System".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 4, pp.3761-3766, URL :https://rjwave.org/ijedr/papers/IJEDR1404062.pdf
Volume 2 Issue 4
Pages. 3761-3766
