http://link.springer.com/article/10.1007/s00779-016-0923-y
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)
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/03/paper-tensor-methods-and-recommender.html
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/personality-as-metric-for-topic-models.html
article: The Future Of Big Data Is Bigger Than You Can Possibly Imagine
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/04/article-future-of-big-data-is-bigger.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
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