PAPER: A Personalized Recommendation Algorithm with User Trust in Social Network

http://link.springer.com/chapter/10.1007/978-981-10-2053-7_7


Please see also:
An Incremental Graph Pattern Matching Based Dynamic Cold-Start Recommendation Method
http://link.springer.com/chapter/10.1007/978-981-10-2053-7_17

PAPER "AN EFFICIENT SIMILARITY-BASED MODEL FOR WEB SERVICE RECOMMENDATION"
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/05/paper-efficient-similarity-based-model.html

PAPER Recommender Systems for the Department of Defense and Intelligence Community
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/07/paper-recommender-systems-for.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) 

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.


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.  


The key to long-lasting romance is STRICT PERSONALITY SIMILARITY, and not "meet other people with similar interests" 
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"