DOIONLINE

DOIONLINE NO - IJAECS-IRAJ-DOIONLINE-2552

Publish In
International Journal of Advances in Electronics and Computer Science-IJAECS
Journal Home
Volume Issue
Issue
Volume-2, Issue-7  ( Jul, 2015 )
Paper Title
A Novel Dynamic Personalized Recommendation Technique For Sparse Data
Author Name
Snehal R. Shinde, Sushila Ratre
Affilition
Department of Computer Engineering, Pillai HOC College of Engineering & Technology, Rasayani, Raigad,India Department of Computer Engineering, Pillai HOC College of Engineering & Technology, Rasayani, Raigad,India
Pages
12-14
Abstract
In E-commerce, sparse data is difficult to manage. Recommendation technique is used to provide dynamic high quality recommendation. If no value exist for given combination of dimension values, no rows exists in fact table. The methods to make use of profiles to extend the co-relating relation, a set to reflect user's preferences or item's reputation are relation mining of rating data, dynamic feature extraction. In Relation mining a semi co-relate relation between items rating and profile content are utilized. Dynamic feature extraction contains set of dynamic features to describe users' multi-phase preferences with respect to computation, accuracy and flexibility. For high quality recommendation adaptive weighting algorithm is proposed with the help of association rule mining. Index terms: Association rule mining, Dynamic recommendation, Dynamic feature extraction, Relation mining
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