A common neighbour based two-way collaborative recommendation method

Authors:
Lin Chen;Richi Nayak;Yue Xu
Affiliations:
Queensland University of Technology, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia;Queensland University of Technology, Brisbane, Australia
Venue:
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Year:
2012

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Abstract

Traditional recommendation methods offer items, that are inanimate and one way recommendation, to users. Emerging new applications such as online dating or job recruitments require reciprocal people-to-people recommendations that are animate and two-way recommendations. In this paper, we propose a reciprocal collaborative method based on the concepts of users' similarities and common neighbors. The dataset employed for the experiment is gathered from a real life online dating network. The proposed method is compared with baseline methods that use traditional collaborative algorithms. Results show the proposed method can achieve noticeably better performance than the baseline methods.