PAPER A Deployed People-to-People Recommender System in Online Dating

http://www.aaai.org/ojs/index.php/aimagazine/article/view/2599
Abstract

Online dating is a prime application area for recommender systems, as users face an abundance of choice, must act on limited information, and are participating in a competitive matching market. This article reports on the successful deployment of a people-to-people recommender system on a large commercial online dating site. The deployment was the result of thorough evaluation and an online trial of a number of methods, including profile-based, collaborative filtering and hybrid algorithms. Results taken a few months after deployment show that the recommender system delivered its projected benefits.

Also related to papers:
PAPER Collaborative filtering for people-to-people recommendation in online dating: data analysis and user trial
http://onlinedatingsoundbarrier.blogspot.com.ar/2014/12/paper-collaborative-filtering-for.html
PAPER Evaluation and Deployment of a People-to-People Recommender in Online Dating
http://onlinedatingsoundbarrier.blogspot.com.ar/2014/08/paper-evaluation-and-deployment-of.html

Please see:
THESIS Recommender Systems for Online Dating
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/09/thesis-recommender-systems-for-online.html

Paper "Recommendation in reciprocal and bipartite social networks - a case study of online dating"
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/01/paper-recommendation-in-reciprocal-and.html

Paper: Recommendation Systems for Markets with Two Sided Preferences
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/01/paper-recommendation-systems-for.html

PAPERS and PRESENTATION from EMPIRE 2015
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/09/papers-and-presentation-from-empire-2015.html

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)

http://onlinedatingsoundbarrier.blogspot.com.ar/2015/08/paper-personalized-recommendation.html 
That is the only way to improve recommender systems, to include the personality traits of their users. They need to calculate personality similarity between users.

In case you had not noticed, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry. 

 Which is the RIGHT approach to innovate in the Personality Based Recommender Systems Arena?
The same approach to innovate in the Online Dating Industry == 16PF5 test or similar to assess personality traits and a new method to calculate similarity between quantized patterns. Oh that is exactly ............ guess ............. yes ........ LIFEPROJECT METHOD, ready since 2001!
All other proposals are NOISE and perform as placebo.
 
Please read: The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html

The Online Dating Industry does not need a 10% improvement, a 50% improvement or a 100% improvement. It does need "a 100 times better improvement", not 100% better, 100X better The Online Dating Industry needs a very powerful algorithm like the "Teller Ulam design". In this case 100 times more powerful than actual matching algorithms.

http://onlinedatingsoundbarrier.blogspot.com.ar/2014/05/lifeproject-method-versus-eharmony.html 

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html
 
What comes after the Social Networking wave?
The Next Big Investment Opportunity on the Internet will be .... Personalization!
Personality Based Recommender Systems and Strict Personality Based Compatibility Matching Engines for serious Online Dating with the normative 16PF5 personality test.
Without offering the NORMATIVE16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.