Anytime Anywhere Information Retrieval and Tracking (AAIRT)
Anytime Anywhere Information Retrieval and Tracking (AAIRT) is a next generation scalable dynamic computational framework for large-scale information and knowledge retrieval and tracking in real-time recently introduced by Eugene Santos, Jr., Eunice E. Santos, Eugene S. Santos and Evelyn W. Santos.
Information acquired by AAIRT, such as structured texts, unstructured texts, video, audio, signals, etc., are all represented in a common form, e.g. concept graph (CG). Depending on the needs, AAIRT can convert the CGs into Bayesian Knowledge fragments (BKF), objects in Augmented Knowledge Base (AKB), objects in Free-Form Database (FFDB) and/or other appropriate forms. BKF is a subset of a Bayesian Knowledge Base (BKB). Since BKFs and objects in AKBs and FFDBs are parts of some knowledge bases, they are amenable to reasoning and inferencing. This allows the possibility of understanding and reasoning involving the results retrieved by AAIRT, and provides the capabilities for dynamically tracking similar information, as well as, related past, current and/or future events.