We describe an approach to unsupervised high-accuracy recognition of the textual contents of an entire book using fully automatic mutual-entropy-based model adaptation. Given imag...
Background: Word sense disambiguation (WSD) is critical in the biomedical domain for improving the precision of natural language processing (NLP), text mining, and information ret...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
We describe an architecture for representing and managing context shifts that supports dynamic data interpretation. This architecture utilizes two layers of learning and three lay...
Nikita A. Sakhanenko, George F. Luger, Carl R. Ste...
Background: High content screening (HCS) is a powerful method for the exploration of cellular signalling and morphology that is rapidly being adopted in cancer research. HCS uses ...
Andrew A. Hill, Peter LaPan, Yizheng Li, Steve Han...