Until recently the state of the art in lossless data compression was prediction by partial
match (PPM). A PPM model estimates the next-symbol probability distribution by combining …

Contemporary information systems are replete with log files, created in multiple places (eg,
network servers, database management systems, user monitoring applications, system …

We developed a fast text compression method based on multiple static dictionaries and
named this algorithm as STECA (Static Text Compression Algorithm). This algorithm is …

Obscuring information in messages to be exchanged over a communications network. In
one aspect, the information comprises path name information and parameters for use in a …

The innate verbosity of the extensible markup language (XML) remains one of its main
weaknesses, especially when large documents are concerned. This problem can be solved …

Semistatic word-based byte-oriented compressors are known to be attractive alternatives to
compress natural language texts. With compression ratios around 30–35%, they allow fast …

Bulk of the streaming data from scientific simulations and experiments consists of numerical
values, and these values often change in unpredictable ways over a short time horizon …

This paper describes a new XML compression scheme that offers both high compression
ratios and short query response time. Its core is a fully reversible transform featuring …

Dictionary-based encoding methods are popular forms of data compression. These methods
were initially implemented to reduce the one-dimensional correlation in data, since they are …

The two last decades have witnessed extensive research on multi-task learning algorithms
in diverse domains such as bioinformatics, text mining, natural language processing as well …