Modeling User Behaviors to Enable Context-Aware Proactive Decision Support

The problem of automatically recognizing a user’s operational context, the implications of its shifting properties, and reacting in a dynamic manner are at the core of mission intelligence and decision making. Environments such as the OZONE Widget Framework (http://www.owfgoss.org) (OWF) provide the foundation for capturing the objectives, actions, and activities of both the mission analyst and the decision maker. By utilizing a “context container” that envelops an OZONE Application, we hypothesize that both user action and intent can be used to characterize user context with respect to operational modality (strategic, tactical, opportunistic, or random). As the analyst moves from one operational modality to another, we propose that information visualization techniques should adapt and present data and analysis pertinent to the new modality and to the trend of the shift. As a system captures the analyst’s actions and decisions in response to the new visualizations, the context container has the opportunity to assess the analyst’s perception of the information value, risk, uncertainty, prioritization, projection, and insight with respect to the current context stage. This paper will describe a conceptual architecture for an adaptive work environment for inferring user behavior and interaction within the OZONE framework, in order to provide the decision maker with context relevant information. We then bridge from our more conceptual OWF discussion to specific examples describing the role of context in decision making. Our first concrete example demonstrates how the Web analytics of a user’s browsing behavior can be used to authenticate users. The second example briefly examines the role of context in cyber security. Our third example illustrates how to capture the behavior of expert analysts in exploratory data analysis, which coupled with a recommender system, advises domain experts of “standard” analytical operations in order to suggest operations novel to the domain, but consistent with analytical goals. Finally, our fourth example discusses the role of context in a supervisory control problem when managing multiple autonomous systems.