Title :
Combined linguistic and sensor models for machine learning
Author_Institution :
Air Force Res. Lab., Wright-Patterson AFB, OH, USA
Abstract :
This work builds on a cognitive theory called dynamic logic and considers the relationship between language and cognition. We explore the idea of dual models that combine linguistic and sensor features. We demonstrate that simultaneous learning of textual and image data results in formation of meaningful concepts and subsequent improvement in concept recognition.
Keywords :
learning (artificial intelligence); pattern recognition; sensor fusion; cognitive theory; concept recognition; dynamic logic; image data learning; linguistic model; machine learning; sensor model; textual data learning; Acceleration; Computational modeling; Data models; Mathematical model; Numerical models; Pragmatics; Vectors; Dynamic Logic; LUPI; Language and Cognition; Unsupervised Learning;
Conference_Titel :
Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
DOI :
10.1109/CCMB.2014.7020690