Sunday, June 12, 2016

PAPER: Incorporating popularity in a personalized news recommender system

https://peerj.com/articles/cs-63.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.
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/04/paper-predicting-personality-traits.html
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?
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.  LIFEPROJECT METHOD  



Please see also:
PAPER "AN EFFICIENT SIMILARITY-BASED MODEL FOR WEB SERVICE RECOMMENDATION"
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/05/paper-efficient-similarity-based-model.html


 
2017 INTERNET TRENDS 2017 Next Big Thing: PERSONALIZATION!
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/06/2017-internet-trends-2017-next-big.html


The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html
 

What comes after the Social Networking wave?
The Next Big Investment Opportunity on the Internet will be .... Personalization!
Personality Based Recommender Systems and Strict Personality Based Compatibility Matching Engines for serious Online Dating with the normative 16PF5 personality test.
Without offering the NORMATIVE16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.
 
All other proposals are NOISE and perform as placebo.


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