Tuesday, March 28, 2017

Data is mother’s milk to Netflix as it tweaks algorithms

to find that perfect content — just like a dating app ???
"The most important work I think we do is around personalization,” said Reed Hastings, the company’s chief executive, during a Q&A session “This idea that the more you watch, the more Netflix learns your tastes. Personalization is really the thing that the Internet can do that linear (distribution) can’t, and that’s a real breakthrough.”

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 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!!! 
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.

How the Big Five (Big 5, OCEAN, or FFI five factor inventory, FFM five factor model ) normative personality test was revealed as .... an incomplete and incorrect model to assess personality ? Short answer: thanks to commingling analysis.
Commingling analysis is a statistical method for distinguishing between one (usually normal) distribution and a mixture of two or more distributions. 


Remember the Netflix Prize ?


(One of) eHarmony CMO: Marketers are getting misled by data attribution

About GDI post "Study Argues Opposites Don’t Attract, Friends & Couples Share Similar Personality Traits"


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