PAPER Using Groups of Items to Bootstrap New Users in Recommender Systems

http://dl.acm.org/citation.cfm?id=2675210
from The 18th ACM conference on Computer-Supported Cooperative Work and Social Computing
March 14-18, 2015 | Vancouver, BC, Canada

http://cscw.acm.org/2015/submit/papers.php

See also:
Personalized recommendations based on time-weighted overlapping community detection
http://www.sciencedirect.com/science/article/pii/S0378720615000191

PAPER Trust-based Service Recommendation in Social Network
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/02/paper-trust-based-service.html
 
Please remember:
Behavioural recommender systems or other system that learns your preferences are useless for serious online dating purposes and 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)
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.
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/02/article-how-dating-companies-are-having.html

If you want to be first in the "personalization arena" == Personality Based Recommender Systems, you should understand HOW TO INNOVATE in the ............ Online Dating Industry first of all!