Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.
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)
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?
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