Phoenix Operations Group will research open-source recommender engines for use in DoD and Intelligence missions. By injecting recommendations into streaming data frameworks (such as Apache Storm and Spark Streaming), recommendations can be made in a real-time context to supporting tipping and cueing functions. Phoenix will also leverage its innovative solutions from the Big Data and Cloud Computing domains so that the system will scale up to support enterprise level data volumes. The high-level architecture is composed of four subsystems: Capture, Analyze, Semantic Search and Display. The Capture subsystem is responsible for ingesting user actions, interaction and transactions. The Analyze subsystem is responsible for generating recommendations, persisting recommendations, and alerting based upon recommendations. The Semantic Search subsystem is responsible for executing user queries and inferring the users true intentions. The Display subsystem is responsible for user interfaces on multiple platforms. The four subsystems work in concert to provide a streaming multi-INT system that can be deployed to individual program platforms or as an enterprise solution.
