Using Hybrid Recommendation to Improve Book Recommendation System
Published: 2016
Author(s) Name: Neetish Chandrakar, Nitin Mishra |
Author(s) Affiliation: Computer Sci & Engineering Rungta College of Engineering & Technology Bhilai, Chhattisgarh, India
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Abstract
Now a days a huge number of users are using the internet. People prefer online shopping for their needs more and more. After doing literature review it is clear that no single algorithm is suitable in every domain some algorithm/method work well in one domain but fail in another domain. So this paper proposes a hybrid recommender method. The proposed method first calculates the correspondence of users from their ratings. Both correspondences among items and users are used for calculating unknown rating of a user to an item. We evaluate the proposed method using a Books data set.
Keywords: Hybrid Recommendation Method, Historical Data, Multidimensional Association Rule, FP-Tree Algorithm
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