User Recommendations in Reciprocal and Bipartite Social Networks--An Online Dating Case Study

Overview of attention for article published in IEEE Intelligent Systems, October 2013

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In the top 5% of all research outputs scored by Altmetric
One of the highest-scoring outputs from this source (#6 of 726)
High Attention Score compared to outputs of the same age (98th percentile)
High Attention Score compared to outputs of the same age and source (90th percentile)

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news: 7 news outlets
blogs: 2 blogs
twitter: 14 X users

googleplus: 1 Google+ user
podcasts: 1 podcast

Readers on

mendeley: 61 Mendeley
citeulike: 1 CiteULike

So far, Altmetric has seen 16 X posts from 14 X users, with an upper bound of 22,313 followers.

Dating is a two-way street — good matches are those that match back. Dr. Kang Zhao’s algorithm takes this into account, and Luna features reciprocal compatibility that’s optimized for mutual success. https://t.co/ptyzASKEA9 #meetluna #machinelearning #…

http://t.co/RnMNY5g1kR User recommendation in reciprocal and bipartite social networks -- a case study of online dating. (arXiv:1311.2...

Researchers Develop Algorithm For Recommending Online Dating Prospects http://t.co/HpfpBpggBy Most... http://t.co/O3js6g1gcK

Interesting approach on #recsys on bipartite reciprocal social networks (http://t.co/Jw7iKROM8Z) include into to CF, for newbies!. #graphdb

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