User talk:Harikrishna/Architecture/Learning Model

According to the current state of the art in context research, this can be divided into two threads:

1. "Perception" (or "user observation") ---> Goal: Gather contextual evidences ---> Realization: User observation modules/components that observe the user's behaviour (desktop actions), track his current location, emotion, whatever more... That's what is what is done with [User Observation Hub]

2. "Context Awareness" (or "context elicitation") ---> Goal: Estimate and model the user's context(s) ---> Realization: The best way of doing this is not yet settled. But by picking and harvesting low-hanging fruits you can already achieve a lot. The most important thing here is to clarify WHAT IS THAT "CONTEXT" ANYWAY? So: Let's start with defining WHAT the context is USED FOR. Your ideas (in previous emails) went in the right direction. Then go over to define, HOW can we MODEL this in an efficient way. At last, we implement some algorithms that fill and update this context model. As I said, the latter part is not yet settled, but don't worry about that now. It will live!