Journal Entry 7-12-20
Today after work I got into studying more about dynamic bayesian networks...It seems that if you could get the rating of personality (personality scale relative to each individual currently in the network) you could begin to rank each person in an ELO system dependent on what their current trajectory (personality prediction) is proportional to their relativity to others.
I suggest the OCEAN ELO Dynamic Bayesian Network System. Not that that rolls of the tongue easily, but I'm just jotting down notes right now it doesn't have to be marketable. Anyways the acronym "OCEAN" just stands for the big 5 personality traits. Then the score would be based on the individual's rating on that scale. This can be used to predict behavior when all combined together into the OCEAN rating algorithm. Essentially this machine learning system would have a unique algorithm for each person that changes with each data entry.
A data entry would be from their daily journalling rating of personality prediction and also any and all social media data that would be mined for analytics.
In the beginning of this system the goals each client picks would be generic and general. Once the system gained more information, goals could be more specialized to each person given similarities to other goals. Essentially the problem to tackle would be how to quantitatively score each qualitative behavior online to predict personality, behavior, and be able to compare and error correct based on the relative behaviors of others.
There's more I want to write, but I have to go to bed now, got work in the morning.