October 23, 2011
"....The Social Web provides huge opportunities for recommender technology and in turn recommender technologies can play a part in fuelling the success of the Social Web phenomenon. The goal of this workshop, the third in the series, is to bring together researcher and practitioners to explore, discuss, and understand challenges and new opportunities for recommender systems and the Social Web. "
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.
Have you seen they need to calculate personality similarity between users?
Have you seen there are different formulas to calculate similarity?
In case you did not notice, recommender systems are morphing to .......... compatibility matching engines!!!
They mostly use the Big5 to assess personality and the Pearson correlation coefficient to calculate similarity.
Researchers in the Personality Based Recommender Systems arena are also testing different / novel formulas to calculate similarity, useless at all because they use the Big5 to assess personality of users.
Online Dating Sites like eHarmony, Parship, Be2, MeeticAffinity, PlentyOfFish Chemistry Predictor and others had been calculating personality similarity between prospective users since several years ago with low successful rates, with a low effectiveness/efficiency level of their matching algorithms (less than 10%) because they use the normative Big5 or ipsative proprietary models instead -like Chemistry or PerfectMatch- to measure personality traits.
No one is using the 16PF5 to assess personality of members.
No one calculates similarity with a quantized pattern comparison method.
No one can show Compatibility Distribution Curves to each and every of its members
See how LIFEPROJECT METHOD calculates similarity.
Similarity in personality patterns with (a proprietary) pattern recognition by correlation method. It takes into account the score and the trend to score of any pattern.