DocumentCode
3431391
Title
Generalization and improvement to PPM´s “blending”
Author
Bunton, Suzanne
Author_Institution
Washington Univ., USA
fYear
1997
fDate
25-27 Mar 1997
Firstpage
426
Abstract
Summary form only given. The best-performing method in the data compression literature for computing probability estimates of sequences on-line using a suffix-tree model is the blending technique used by PPM. Blending can be viewed as a bottom-up recursive procedure for computing a mixture, barring one missing term for each level of the recursion, where a mixture is basically a weighted average of several probability estimates. The author shows the relative effectiveness of most combinations of mixture weighting functions and inheritance evaluation times. The results of a study on the value of using update exclusion, especially in models using state selection, are also sown
Keywords
data compression; probability; recursive estimation; PPM; blending technique; bottom-up recursive procedure; data compression; inheritance evaluation times; mixture weighting functions; probability estimates; sequences; state selection; suffix-tree model; update exclusion; weighted average; Data compression; Recursive estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference, 1997. DCC '97. Proceedings
Conference_Location
Snowbird, UT
ISSN
1068-0314
Print_ISBN
0-8186-7761-9
Type
conf
DOI
10.1109/DCC.1997.582082
Filename
582082
Link To Document