A Collaborative Approach for Web Personalized Recommendation System

  Nirav M. Khetra,  Shruti B. Yagnik

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.

Keywords- Recommendation, Typicality, Collaborative Filtering

Unique Identification Number - IJEDR1404062
Page Number(s) - 3761-3766
Pubished in - Volume 2 | Issue 4 | Dec 2014
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Nirav M. Khetra,  Shruti B. Yagnik,   "A Collaborative Approach for Web Personalized Recommendation System", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 4, pp.3761-3766, Dec 2014, Available at :http://www.ijedr.org/papers/IJEDR1404062.pdf