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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
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← Back to VOLUME 5, ISSUE 7, JULY 2016

Recommendation System Using Collaborative Filtering Technology

Miss. Harshali U. Chaudhary, Prof. Priti Subramanium

DOI: 10.17148/IJARCCE.2016.5721

Abstract: Recommendation systems are used to predict the �rating' or �preference' that user would give to an item and are applied in a variety of applications like music, movies, news, research articles, books, social tags, search queries and products in general. In this paper, author has given investigation on the cooperative filtering recommendation from a brand new perspective and presents a completely unique typicality-based cooperative filtering recommendation technique named Tyco. 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.



Keywords: Recommendation System, Travel Package, Fuzzy C-means clustering.

How to Cite:

[1] Miss. Harshali U. Chaudhary, Prof. Priti Subramanium, “Recommendation System Using Collaborative Filtering Technology,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2016.5721