PAPER: Personality and Recommendation Diversity

http://link.springer.com/chapter/10.1007/978-3-319-31413-6_11

Emotions and Personality in Personalized Services.
Part of the series Human–Computer Interaction Series pp 201-225
Date: 14 July 2016

Please see also:
Personality-Based User Modeling for Music Recommender Systems
http://www.bruceferwerda.com/papers/2016_Ferwerda_etal_NECTAR.pdf  
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"