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General Information
    • ISSN: 1793-8244
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Dr. Ka Wai Gary Wong
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), Engineering & Technology Digital Library, DOAJ, Electronic Journals Library, Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Editor-in-chief
Dr. Ka Wai Gary Wong
Division of Information and Technology Studies, Faculty of Education, The University of Hong Kong.
It's a honor to serve as the editor-in-chief of JACN. I'll work together with the editors and reviewers to help the journal progress
JACN 2015 Vol.3(3): 251-254 ISSN: 1793-8244
DOI: 10.7763/JACN.2015.V3.177

UIIM: A User-Item Interest Model Based on Bipartite Network for Top-N Recommender System

Zhixiong Jiang, Chunyang Lu, Siyuan Zheng, and Juan Yang
Abstract—Recently, a sparse linear method (SLIM) is developed for top-N recommender systems, which can produce high-quality recommendations for sparse data sets. SLIM provides a better performance than other existing methods. In this paper, we provide a novel user-item interest method (UIIM) based on bipartite network to improve the performance of SLIM. UIIM generates top-N recommendations by building the user-item interest matrix R with the bipartite network of users and items, calculating the item-item similarity matrix W with SLIM and predicting users’ ratings on items as a dot product of matrix R and W. And we also provide a parallel algorithm based on Spark to learn W. Our results indicate that UIIM provides better performance and recommendation quality than other existing methods and parallel algorithm of learning W outperforms serial algorithm on large-scale data sets.

Index Terms—Top-N recommender systems, bipartite network, UIIM, SLIM, parallel.

Zhixiong Jiang and Chunyang Lu are with CNPC Changping Data Center, Beijing 102206, China (e-mail: jiangzhixiong@cnpc.com.cn, luchunyang@cnpc.com.cn).
Siyuan Zheng and Juan Yang are with Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China (e-mail: zsybupt@gmail.com, yangjuan@bupt.edu.cn).

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Cite:Zhixiong Jiang, Chunyang Lu, Siyuan Zheng, and Juan Yang, "UIIM: A User-Item Interest Model Based on Bipartite Network for Top-N Recommender System," Journal of Advances in Computer Networks vol. 3, no. 3, pp. 251-254, 2015.

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