Improving matching process in social network

, , & (2010) Improving matching process in social network. In Wu, X, Fan, W, Hsu, W, Liu, B, Webb, G I, Zhang, C, et al. (Eds.) Proceedings of the 10th IEEE International Conference on Data Mining Workshops. IEEE Computer Society, United States, pp. 305-311.

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Description

Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

Impact and interest:

8 citations in Scopus
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ID Code: 40175
Item Type: Chapter in Book, Report or Conference volume (Conference contribution)
ORCID iD:
Nayak, Richiorcid.org/0000-0002-9954-0159
Xu, Yueorcid.org/0000-0002-1137-0272
Measurements or Duration: 7 pages
Keywords: Clustering, Online Dating, SimRank
DOI: 10.1109/ICDMW.2010.41
ISBN: 978-0-7695-4257-7
Pure ID: 32162085
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > QUT Faculties & Divisions > Science & Engineering Faculty
Current > Research Centres > Australian Research Centre for Aerospace Automation
Copyright Owner: Consult author(s) regarding copyright matters
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Deposited On: 17 Feb 2011 01:02
Last Modified: 02 Mar 2024 00:19