No matter what specific methodology you employ, this in-depth looking system helps you to compress the file rather more effectively than you could by just selecting words. And to cut back the file measurement as much as possible, it fastidiously selects which patterns to incorporate in the dictionary. If we method the phrase from this perspective, we find ourselves with a completely different dictionary. We already noticed that the entire phrase takes up to seventy-nine models. The phrase “can do for” is also repeated, one time followed by “your” and one time followed by “you,” giving us a repeated sample of “can do for you.” This lets us write 15 characters including spaces with one number worth, whereas “your country” solely lets us write 13 characters with areas with one number worth, so the program would overwrite the “your nation” entry as simply “r nation,” and then write a separate entry for “can do for you.” The program proceeds in this fashion, choosing all repeated bits of knowledge and then calculating which patterns it should write to the dictionary.
In “ask not what your,” there’s a repeated sample of the letter “t” followed by an area — in “not” and “what.” If the compression program wrote this to the dictionary, it could write a “1” every time a Digital Shop “t” had been adopted by a space. You’ll be able to imagine that if the compression program worked for the rest of Kennedy’s speech, it might discover these phrases and others repeated many extra times. However, a compression program sees it differently: It does not have any concept of different phrases — it solely appears for patterns. In a particular compression scheme, figuring out the varied file requirements can be fairly difficult; however, for our functions, let’s return to the idea that each character and house takes up one unit of memory.
Otherwise, you’ll be starting over while you get it again. And, as we’ll see in the subsequent section, it would be rewriting the dictionary to get the best organization possible. The next thing this system might notice is “ou,” which seems in both “your” and “country.” If this were a longer document, scripting this pattern to the dictionary could save numerous space — “ou” is a fairly widespread mixture within the English language. This system supplies a seemingly limitless technique of expressing concepts through its many options and features while additionally serving to the writer set up his ideas. But on this quick-phrase, this pattern does not happen sufficient to make it a worthwhile entry, so this system would eventually overwrite it.