Gzip versus bag-of-words for text classification

Juri Opitz

Gzip versus bag-of-words for text classification

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arxiv 2307.15002 v5 pith:SM4ORUDE submitted 2023-07-27 cs.CL

Juri Opitz This is my paper

classification cs.CL

keywords bag-of-wordsclassificationgziptextachieveapproachesattentionbetter

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The effectiveness of compression in text classification ('gzip') has recently garnered lots of attention. In this note we show that `bag-of-words' approaches can achieve similar or better results, and are more efficient.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Text Distance from Nested and Hierarchical Repetitions: A Compression-Based Perspective
cs.CL 2026-06 conditional novelty 6.0 of 10

Ladderpath-derived distances (NCD_lp, L_Dice, L_Jaccard) with k-NN outperform gzip-NCD and BERT on out-of-distribution and few-shot text classification without training.

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