Title :
Inquisitive pattern recognition
Author :
Magnus, Amy L. ; Gustafson, Steven C.
Author_Institution :
Rome Res. Site, Intelligent Inf. AFRL/IFTD, Rome, NY, USA
Abstract :
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.
Keywords :
knowledge based systems; pattern recognition; sensor fusion; unsupervised learning; conflict identification; conflict resolution; conflicting information; cross-validation; data fusion; experience acquisition; falsification; feature-space confusion classification; inquisitive pattern recognition; knowledge base; multi-source multi-modal data; persistent unsupervised learning capability; relevance; situation assessment; Bandwidth; Information management; Intellectual property; Knowledge representation; Multimodal sensors; Pattern recognition; Sensor systems; Signal to noise ratio; Space technology; Unsupervised learning;
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
DOI :
10.1109/IFIC.2000.862459