Text Compression Via Alphabet Re-Representation

d abstract Philip M. Long Apostol I. Natsevy Je rey Scott Vittery We consider re-representing the alphabet so that a representation of a character re ects its properties as a predictor of future text. This enables us to use an estimator from a restricted class to map contexts to predictions of upcoming characters. We describe an algorithm that uses this idea in conjunction with neural networks. The performance of this implementation is compared to other compression methods, such as UNIX compress, gzip, PPMC, and an alternative neural network approach.

• Type: Conference
• Year: 1997
• Where: DCC
• Authors: Philip M. Long, Apostol Natsev, Jeffrey Scott Vitter
• Keywords: Abstract Philip M, Computer Graphics, DCC 1997, Je Rey Scott, Neural Network