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Open AccessArticle

A Hybrid Two-Phase Recommendation for Group-Buying E-commerce Applications

by Li Bai 1, Mi Hu 2, Yunlong Ma 2 and Min Liu 2,*
1
School of Accounting, Shanghai Lixin University of Accounting and Finance, Shanghai 201602, China
2
College of Electrical Information and Engineering, Tongji University, Shanghai 201804, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(15), 3141; https://doi.org/10.3390/app9153141
Received: 27 June 2019 / Revised: 19 July 2019 / Accepted: 31 July 2019 / Published: 2 August 2019
The last two decades have witnessed an explosive growth of e-commerce applications. Existing online recommendation systems for e-commerce applications, particularly group-buying applications, suffer from scalability and data sparsity problems when confronted with exponentially increasing large-scale data. This leads to a poor recommendation effect of traditional collaborative filtering (CF) methods in group-buying applications. In order to address this challenge, this paper proposes a hybrid two-phase recommendation (HTPR) method which consists of offline preparation and online recommendation, combining clustering and collaborative filtering techniques. The user-item category tendency matrix is constructed after clustering items, and then users are clustered to facilitate personalized recommendation where items are generated by collaborative filtering technology. In addition, a parallelized strategy was developed to optimize the recommendation process. Extensive experiments on a real-world dataset were conducted by comparing HTPR with other three recommendation methods: traditional CF, user-clustering based CF, and item-clustering based CF. The experimental results show that the proposed HTPR method is effective and can improve the accuracy of online recommendation systems for group-buying applications. View Full-Text
Keywords: e-commerce; group-buying; online recommendation; clustering; collaborative filtering e-commerce; group-buying; online recommendation; clustering; collaborative filtering
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Bai, L.; Hu, M.; Ma, Y.; Liu, M. A Hybrid Two-Phase Recommendation for Group-Buying E-commerce Applications. Appl. Sci. 2019, 9, 3141.

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