Inquisitive pattern recognition
Amy L. Magnus, Steven C. Gustafson · 2000
In nature, inquisitiveness is the drive to question, to seek a deeper understanding and to challenge assumptions. Within the discrete world of computers, inquisitive pattern recognition (IPR) is the constructive investigation and exploitation of conflict in information. Data fusion is fertile proving-ground for inquisitive technologies. Multi-source, multi-modal data inherently contain conflicting information. As data fusion advances capabilities in situation assessment, strategies to identify and resolve conflict become important. IPR is a persistent, unsupervised learning capability whose concepts include falsification-similar to the supervised learning technique of cross-validation-and the classification of confusion in feature space. Coupled with knowledge base technologies, IPR enables a computer to acquire new experiences.