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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2018 Vol.8(3): 223-228 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.3.691

Implicative Rating-Based Hybrid Recommendation Systems

Lan Phuong Phan, Hung Huu Huynh, and Hiep Xuan Huynh
Abstract—This paper proposes the implicative rating measures built on the statistical implicative measures. The paper also proposes the hybrid recommendation model - the combination of the user-based collaborative filtering approach and the association rule based approach using the implicative rating measures - to suggest a list of top N items to active users. The proposed hybrid model are compared to some existing models on two datasets MSWeb and CourseRegistraion. The experimental results show that the performance of the proposed model is higher than that of the compared models.

Index Terms—Implicative rating measure, hybrid recommendation model, user-based collaborative filtering, association rule.

Lan Phuong Phan is with Can Tho University of Technology (CTUT), Vietnam (e-mail: pplan@cit.ctu.edu.vn).


Cite: Lan Phuong Phan, Hung Huu Huynh, and Hiep Xuan Huynh, "Implicative Rating-Based Hybrid Recommendation Systems," International Journal of Machine Learning and Computing vol. 8, no. 3, pp. 223-228, 2018.

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