Managing Analysis Context

Modern intelligence analysis often involves a complex, iterative, highly branched sequence of information gathering and processing steps. Analysts can benefit greatly from Mind Snaps, semantic bookmarks that would allow them to return to a particular point in the analysis and recreate the complete context they had at that time. This paper addresses some basic issues related to creating and maintaining Mind Snaps. One issue is how frequently we need to take a Mind Snap. Our experiment shows that 10 to 30 analyst events offer 85 percent to 95 percent precision in the ability to distinguish analysts working on different tasks. This translates into an interval for taking Mind Snaps that should be between five to 15 minutes. Another important issue the paper addresses is how to separate actions into multiple micro-contexts in an environment where the analyst often concurrently engages in multiple tasks. The key to this issue is the ability to detect the change in contexts, i.e., context switch. We have developed an algorithm for separating context based on user modeling. Our experiment uses this algorithm to demonstrate the feasibility of capturing and disentangling the analytic micro-contexts. In particular, our results show that context switches can be successfully detected using as few as 10 analysis log event (ALE) windows. Better detection is achieved with larger windows. At a widow size of 30 ALE, we achieved a precision of 73 percent and a recall of 70 percent.