Compressing Texts with Neural Nets
نویسنده
چکیده
Neural networks are promising tools for data compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text les. We apply our methods to certain short newspaper articles and obtain compression ratios exceeding those of widely used Lempel-Ziv algorithms (which are the basis of the UNIX functions \compress" and \gzip"). Our methods' main disadvantage is that they are about three orders of magnitude slower than standard methods.
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