However, this doesn't beat general Brotli encoding of a ASCII trie representation, which gets down to 14,180 bytes (but needs an experience decoder), but goes to show general purpose compression is still really really good these days.
However, this doesn't beat general Brotli encoding of a ASCII trie representation, which gets down to 14,180 bytes (but needs an experience decoder), but goes to show general purpose compression is still really really good these days.
[1] https://lifthrasiir.github.io/roadroller/ (the exact parameters: golf.horse dataset; input mode text; action write to document; # contexts 12 with 12,15,49,50,70,79,96,97,131,154,292,353; pollute the global scope; max memory usage 150 MB; precision 16; learning rate 1333; model max count 11; model base divisor 14; dynamic model flags -1; # abbreviations 64)
It compresses better with new lines than if you remove them all (given you could just split on every 5 characters later), which is an odd quirk of compression algorithms that my brain will never quite grasp.
My best algorithm attempt + Brotli achieved 12,773 bytes, which is a painfully close 542 bytes away. It is 13,181 bytes raw though, and can technically be used in-memory, which is definitely a perk.
New lines give a usable context (namely the word boundary) to compression algorithms. If I give you an arbitrary unsorted list of 5-letter-long words with no delimiters you need to think harder to figure out that it is indeed a list of 5-letter-long words. Same for the compression algorithm.
> My best algorithm attempt + Brotli achieved 12,773 bytes, which is a painfully close 542 bytes away. It is 13,181 bytes raw though, and can technically be used in-memory, which is definitely a perk.
Yeah, the best solution depends on what you want to do with that. Your estimation is not too far from my experience: Roadroller tends to be on par with or slightly smaller than Brotli. Of course, Roadroller exists because web browsers generally don't provide a way to use Brotli in JS ;-)
The usual application involves letter frequencies without context. Rather than a trie for deterministic context, one could in far less space compute a hidden Markov chain of small but effective dimension, to generate the probabilities for arithmetic coding.
A lot can be done in 3014 bytes, but what's the difference in code size for the ascii trie vs. a flat list/gzip/brotli?