Paper Info
Title
Low-complexity compression of short messages
Abstract
We describe a low-complexity scheme for lossless compression of short text messages. The method uses arithmetic coding and a specific statistical context model for prediction of single symbols. Our particular contribution is a simple yet effective approach for storing highly complex statistics in a succinct yet effective data model that can easily be trained by text data. The proposed model already gives good compression rates with a RAM memory size of 128 kByte, thus making lossless data compression with statistical context modeling readily applicable to small devices like wireless sensors or mobile phones.
Year
DOI
Venue
2006
10.1109/DCC.2006.45
Snowbird, UT
Keywords
Field
DocType
arithmetic codes,data compression,electronic messaging,mobile handsets,random-access storage,statistical analysis,wireless sensor networks,RAM memory,arithmetic coding,data compression,lossless compression,low-complexity compression,mobile phones,short text messages,specific statistical context model,wireless sensors
Lossy compression,Computer science,Prediction by partial matching,Context model,Theoretical computer science,Data compression,Image compression,Arithmetic coding,Context-adaptive binary arithmetic coding,Lossless compression
Conference
ISSN
ISBN
Citations 
1068-0314
0-7695-2545-8
5
PageRank 
References 
Authors
0.65
10
3
Name
Order
Citations
PageRank
Stephan Rein1837.48
Clemens Guhmann281.46
F. H.P. Fitzek368956.23