Monday, June 20, 2016

PAPER Design of reciprocal recommendation systems for online dating

from same authors of
Predicting User Replying Behavior on a Large Online Dating Site
Who is Dating Whom: Characterizing User Behaviors of a Large Online Dating Site.

But, unfortunately ..... big data dating IS NOT the key to long-lasting romance

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.

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?

he 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.
See How LIFEPROJECT METHOD calculates similarity between quantized patterns using an adapted quantum mechanics math equation same as "Teller Ulam design".  
LIFEPROJECT METHOD is like the "Teller Ulam design" for the Online Dating Industry.
In this case 100 times more powerful than actual matching algorithms.

Not 100% better, 100 TIMES better

All other proposals are NOISE and perform as placebo.


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