Computer-mediated synchronous communication (chat) is becoming an increasingly important tool for gaining and maintaining situation awareness in military operations. Our primary goal in this project is to investigate the ways in which text extraction technology can help in the kind of C2 Chat setting exemplified by Air Operations Centers' (AOC) dynamic targeting cells (DTC). The difficulties inherent in maintaining situation awareness in this fast paced and information rich environment can be addressed by improving training to make more effective use of existing tools, and by improving the existing tools themselves to help operators leverage their scarce attentional resources. We believe that text extraction technology adapted to C2 Chat will materially improve both off-line performance analysis and on-line information management. Janya and Aptima have already developed tools for dealing with Command and Control (C2) Chat. These two tools complement each other, allowing for a more comprehensive approach to managing C2 Chat. Janya's Semantex Chat Processor (Semantex/Chat) supports the real time recognition of entities, events and relationships mentioned in the chat stream. Aptima's Communications and Information Flow Tracking System (CIFTS) can analyze chat logs off line at a higher level, to identify patterns of communication supporting sophisticated performance analysis tools.
Benefit: The ability to automatically annotate key items of information appearing in a chat message stream will help operators using this popular communication and collaboration tool to better follow the contents of multiple simultaneous conversations. Key information will be easier to spot, easier to retain, easier to share, and easier to integrate into a big picture view.
Keywords: Chat, Text Extraction, Performance Assessment, Knowledge Formation, Facilitate Reporting, Ttp, Aoc, Caoc-N, Semi-Supervised Learning; Unsupervised Learning
