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Towards Better Compressed Representations

Abstract: 

We introduce the problem of computing a parsing where each phrase is of length at most m and which minimizes the zeroth order entropy of parsing. Based on the recent theoretical results we devise a heuristic for this problem. The solution has straightforward application in succinct text representations and gives practical improvements. Moreover the proposed heuristic yields structure which size can be bounded both by |S|H_{m-1}(S) and by |S|/m(H_0(S) + ... + H_{m-1}(S)),where H_{k}(S) is the k-th order empirical entropy of S. We also consider a similar problem in which the first-order entropy is minimized.

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Paper Details

Authors:
Michał Gańczorz
Submitted On:
25 March 2020 - 1:11pm
Short Link:
Type:
Poster
Event:
Presenter's Name:
Michał Gańczorz
Paper Code:
152
Session:
Posters

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poster_dcc.pdf

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[1] Michał Gańczorz, "Towards Better Compressed Representations", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5029. Accessed: Mar. 30, 2020.
@article{5029-20,
url = {http://sigport.org/5029},
author = {Michał Gańczorz },
publisher = {IEEE SigPort},
title = {Towards Better Compressed Representations},
year = {2020} }
TY - EJOUR
T1 - Towards Better Compressed Representations
AU - Michał Gańczorz
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5029
ER -
Michał Gańczorz. (2020). Towards Better Compressed Representations. IEEE SigPort. http://sigport.org/5029
Michał Gańczorz, 2020. Towards Better Compressed Representations. Available at: http://sigport.org/5029.
Michał Gańczorz. (2020). "Towards Better Compressed Representations." Web.
1. Michał Gańczorz. Towards Better Compressed Representations [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5029