Thursday, August 25, 2016
PAPER Personalized User Profiling for Time-Dependent Recommendation of Structured Products
PAPER: Enhanced user modeling based on link attributes for recommendation system
PAPER: A Collaborative Filtering Recommender Algorithm Based on Privacy Preserving
PAPER User Similarity Adjustment for Improved Recommendations
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)
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.
High precision in matching algorithms is precisely the key to open the door and leave the infancy of compatibility testing.
Without offering the NORMATIVE 16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.
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"
All other proposals are NOISE and perform as placebo.