RECOMMENDER ALGORITHMS BASED ON BOOSTING ENSEMBLE LEARNING

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic

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VOLUME 8 , ISSUE 1 (March 2015) > List of articles

RECOMMENDER ALGORITHMS BASED ON BOOSTING ENSEMBLE LEARNING

Cheng Lili

Keywords : Recommended System, Ensemble learning, Collaborative filtering, boosting.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 1, Pages 368-386, DOI: https://doi.org/10.21307/ijssis-2017-763

License : (CC BY-NC-ND 4.0)

Received Date : 22-October-2014 / Accepted: 15-January-2015 / Published Online: 01-March-2015

ARTICLE

ABSTRACT

This article introduces ensemble learning algorithms in recommender systems, and in boosting algorithm framework of this article, shows how to filter the basic recommendation
algorithm according to the characteristics of boosting algorithm. By comparing the rational choice of the two recommended boosting algorithm is applied to the frame. And then it determines the main parameters of the algorithm through the experiments, ultimately to obtain a more effective integration of the recommendation algorithm. Experimental results on Netflix validate the effectiveness of the proposed algorithm.

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