Wednesday, May 17, 2017

AI, former eHarmony's Chief Scientist and PsyML (machine learning and big data)




http://www.puromarketing.com/12/28785/como-inteligencia-artificial-quiere-ayudar-marcas-encontrar-influencers.html
https://www.linkedin.com/in/j-galen-buckwalter-04139510
http://psyml.co/about/

PAPER: Improved collaborative filtering recommendation algorithm of similarity measure
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/05/paper-improved-collaborative-filtering.html

article: Secret of eHarmony algorithm is ignoring wishes of picky daters
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/05/article-secret-of-eharmony-algorithm-is.html

article: How successful is digital dating in finding ‘The One’?
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/04/article-how-successful-is-digital.html



PAPER: Twitter User Personality Prediction 2017
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/04/paper-twitter-user-personality.html

IBM Deciphers Personality Types From 200 Tweets ?
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/11/ibm-deciphers-personality-types-from.html

Finally the perfect dating algorithm? Of course NOT, Big Five test is OBSOLETE.
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/02/finally-perfect-dating-algorithm-of.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.
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/01/paper-comparative-study-of-people-to_14.html  

They need to calculate personality similarity between users but there are different formulas to calculate similarity.

In case you did not notice, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates until now because they mostly use the Big Five model to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old. 


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.
Online Dating sites have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 test instead and another method to calculate similarity.

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

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