loading...
On Non-sequential Context Modeling with Application to Executable Data Compression
March 25-March 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DCC.2008.6Data Compression Conference (dcc 2008)
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
The sequential context modeling framework is generalized to a non-sequential one by context relaxation from consecutive suffix of the subsequences of symbols to the permutation of the preceding symbols as result of considering complex context structures in such sources as video and program binaries. Context weighting tree is also extended to a series of context trees which are built according to the “model tree”, in which the descendent relationship in the formation of non-sequential context sets is described. Model redundancy and maximum a posteriori model in the framework are discussed and compared. A decision method based on the greedy algorithm is proposed to customize sets of models fitting the concrete sources. Brief description of application to executable data files incorporating with the semantics and syntax constraints are given and experiment are made accordingly as a validation.
Index Terms:
Sequential context modeling, Prediction by Partial Match, MDL, data compression, maximum a posteriori
Citation:
Wenrui Dai, Hongkai Xiong, Li Song, "On Non-sequential Context Modeling with Application to Executable Data Compression," dcc, pp.172-181, Data Compression Conference (dcc 2008), 2008
Usage of this product signifies your acceptance of the Terms of Use.