Computer Science ›› 2025, Vol. 52 ›› Issue (11A): 241000081-6.doi: 10.11896/jsjkx.241000081

• Big Data & Data Science • Previous Articles     Next Articles

Label Data Compression Algorithms Based on BWT,MTF and ANS

LIAO Rui, TANG Jie, LIANG Tongjia, ZHENG Xinlei, WANG Binyi, QI Zhiqiang   

  1. Northwest Institute of Mechanical and Electrical Engineering,Xianyang,Shaanxi 712099,China
  • Online:2025-11-15 Published:2025-11-10

Abstract: Using some rule sets it is possible to convert some information into specific content stored in a labeling code of a certain length.When there is a lot of information,it is more difficult to use the labeling code.Compression of tag code data can reduce the overhead of storing information and facilitate identification.In order to realize the compression of such data,this paper improves ANS based on BWT and MTF to form a lossless compression algorithm applicable to labeled data,which provides lossless data compression of labeled code to a certain extent,which is conducive to the storage and identification of labeled code information and promotes the use of labeled code.

Key words: Tag data, Lossless data compression, BWT transform, Move-to-front transform, Asymmetric Numeral Systems

CLC Number: 

  • TP391
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