Saturday, May 14, 2016
PAPER Recommendations beyond the Ratings Matrix
Please see also:
PAPER Recommender System with Composite Social Trust Networks
PAPER Identifying Opportunities for Valuable Encounters: Toward Context-Aware Social Matching Systems
PAPER Recommender Systems supporting Decision Making through Analysis of User Emotions and Personality
PAPER Personalized Recommendation Combining User Interest and Social Circle
PAPER Online social trust reinforced personalized recommendation
BOOK: Recommender Systems, The Textbook
PAPER: Trinity: Walking on a User-Object-Tag Heterogeneous Network for Personalised Recommendations
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.
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