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A common neighbour based two-way collaborative recommendation method

Published: 26 March 2012 Publication History

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.

References

[1]
Diaz, F., Metzler, D., & Yahia, S. A. (2010). Relevance and Ranking in Online Dating Systems. Paper presented at the SIGIR'10, 66--73.
[2]
Linden, G. S., & York, J. (2003). Amazon.com Recommenation Item-to-Item Collaborative Filtering. IEEE Internet Computing, 76--80.
[3]
Chen. L., et al., (2011) "Social Network Analysis on Online Dating Network" CT'2011, 41--49.
[4]
L. Admic and E. Adar. Friends and Neighbors on the Web, vol. 25, pp. 211--230, 2001.
[5]
J. L. Herlocker et. al., An Algorithmic Framework for Performing Collaborative Filtering. Presented at SIGIR'99, pp. 230--237, 1999.

Cited By

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  • (2023)An Innovative Two-way Recommender System for Students and Teachers2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10307697(1-5)Online publication date: 6-Jul-2023
  • (2020)Reciprocal Recommender Systems: Analysis of state-of-art literature, challenges and opportunities towards social recommendationInformation Fusion10.1016/j.inffus.2020.12.001Online publication date: Dec-2020
  • (2014)Two-way Recommendation Methods for Social NetworksProceedings of the 7th Workshop on Ph.D Students10.1145/2663714.2668054(33-34)Online publication date: 3-Nov-2014

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Published In

cover image ACM Conferences
SAC '12: Proceedings of the 27th Annual ACM Symposium on Applied Computing
March 2012
2179 pages
ISBN:9781450308571
DOI:10.1145/2245276
  • Conference Chairs:
  • Sascha Ossowski,
  • Paola Lecca

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 March 2012

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Author Tags

  1. online dating
  2. reciprocal
  3. recommendation system
  4. user preference
  5. user profile

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SAC 2012
Sponsor:
SAC 2012: ACM Symposium on Applied Computing
March 26 - 30, 2012
Trento, Italy

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SAC '12 Paper Acceptance Rate 270 of 1,056 submissions, 26%;
Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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SAC '25
The 40th ACM/SIGAPP Symposium on Applied Computing
March 31 - April 4, 2025
Catania , Italy

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Cited By

View all
  • (2023)An Innovative Two-way Recommender System for Students and Teachers2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10307697(1-5)Online publication date: 6-Jul-2023
  • (2020)Reciprocal Recommender Systems: Analysis of state-of-art literature, challenges and opportunities towards social recommendationInformation Fusion10.1016/j.inffus.2020.12.001Online publication date: Dec-2020
  • (2014)Two-way Recommendation Methods for Social NetworksProceedings of the 7th Workshop on Ph.D Students10.1145/2663714.2668054(33-34)Online publication date: 3-Nov-2014

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