PAPER Recommender Systems supporting Decision Making through Analysis of User Emotions and Personality

Recommender Systems supporting Decision Making through Analysis of User Emotions and Personality

"Abstract. The influence of emotions in decision making is a popular research topic in psychology and cognitive studies. A person facing a choosing problem has to consider different solutions and take a decision. During this process several elements in
fluence the reasoning, some of them are rational, others are irrational, such as emotions.
Recommender Systems can be used to support decision making by narrowing the space of options. Typically they do not consider irrational elements during the computational process, but recent studies show that accuracy of suggestions improves whether user's emotional state is included in the recommendation process.
In this paper we propose the idea of defining a framework for an Emotion-Aware Recommender System. The user emotions will be formalized in an a ective user profile which can act as an emotional computational model. The Recommender System will
use the affective profile integrated with case base reasoning to compute recommendations."

presented at 14th Conference of the Italian Association for Artificial Intelligence, Ferrara
http://aixia2015.unife.it/dc-accepted-papers/

http://www.slideshare.net/MarcoPolignano/recommender-systems-supporting-decision-making-through-analysis-of-user-emotions-and-personality

PAPER A Deployed People-to-People Recommender System in Online Dating
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/10/paper-deployed-people-to-people.html
EMPIRE 2013: Emotions and Personality in Personalized Services
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/empire-2013-emotions-and-personality-in.html

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/2015/08/paper-personalized-recommendation.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.

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. Oh that is exactly ............ guess ............. yes ........ LIFEPROJECT METHOD, ready since 2001!
All other proposals are NOISE and perform as placebo.