Effective Hybrid Recommender Approach using Improved K-means And Similarity

International Journal of Computer Trends and Technology (IJCTT)          
© 2016 by IJCTT Journal
Volume-36 Number-3
Year of Publication : 2016
Authors : Prerana Khurana, Shabnam Parveen
DOI :  10.14445/22312803/IJCTT-V36P126


Prerana Khurana, Shabnam Parveen "Effective Hybrid Recommender Approach using Improved K-means And Similarity". International Journal of Computer Trends and Technology (IJCTT) V36(3):147-152, June 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In this age of information load, it become a herculean task for user to get the relevant information. Recommender system plays an important role in suggesting relevant information that is likely to be preferred by the user. Different type of clustering is used for recommender system like K-means, fuzzy C-mean, chameleon hierarchical etc. This papers aims at proposing a recommender system that uses hybrid approach using improved K-means clustering with Spearman’s rank correlation similarity to reduce the RMSE and time complexity and results are compared with basic K-means clustering.

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Recommender System, Hybrid Recommender, clustering, k-means, similarity, RMSE, Spearman`s rank correlation.