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Asked: 2026-06-13T02:47:45+00:00

I have 3 main questions: Let’s say I have a large text file. (1)Is

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I have 3 main questions:

Let’s say I have a large text file. (1)Is replacing the words with their rank an effective way to compress the file? (Got answer to this question. This is a bad idea.)

Also, I have come up with a new compression algorithm. I read some existing compression models that are used widely and I found out they use some pretty advanced concepts like statistical redundancy and probabilistic prediction. My algorithm does not use all these concepts and is a rather simple set of rules that need to be followed while compressing and decompressing. (2)My question is am I wasting my time trying to come up with a new compression algorithm without having enough knowledge about existing compression schemes?

(3)Furthermore, if I manage to successfully compress a string can I extend my algorithm to other content like videos, images etc.?

(I understand that the third question is difficult to answer without knowledge about the compression algorithm. But I am afraid the algorithm is so rudimentary and nascent I feel ashamed about sharing it. Please feel free to ignore the third question if you have to)

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1 Answer

  1. Editorial Team

    1. Your question doesn’t make sense as it stands (see answer #2), but I’ll try to rephrase and you can let me know if I capture your question. Would modeling text using the probability of individual words make for a good text compression algorithm? Answer: No. That would be a zeroth order model, and would not be able to take advantage of higher order correlations, such as the conditional probability of a given word following the previous word. Simple existing text compressors that look for matching strings and varied character probabilities would perform better.

    2. Yes, you are wasting your time trying to come up with a new compression algorithm without having enough knowledge about existing compression schemes. You should first learn about the techniques that have been applied over time to model data, textual and others, and the approaches to use the modeled information to compress the data. You need to study what has already been researched for decades before developing a new approach.

    3. The compression part may extend, but the modeling part won’t.

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