I'm working on a similar idea, but as a way to predict personality temperament. The idea is to use a simple SVM from machine learning and code multiple context

I'm working on a similar idea, but as a way to predict personality temperament. The idea is to use a simple SVM from machine learning and code multiple contextual inputs into the feature vector. The resulting labels correspond to a users personality. An example would be that on Friday (5) at 10 am (36000) in San Francisco (94158) etc that input maps to personality temperament. My work is still also in the preliminary stages but I have a working prototype on iOS that captures over 200 contextual inputs across 14 sensor categories which get factored into the algorithm. Right now, the contextual vectors are used to predict someones personality temperament, but I never thought about mapping them to thoughts.