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As a poweruser of Algernon, I want to be able to use shortened versions of Hotwords in order to work faster by typing less.
Possible implementations:
Acronyms for hotwords
use b for browse, h for help, etc.
-> This is more to memorize, as some hotword acronyms might overlap if we just choose the first letter. This might also require changes in the future if more hotwords are added.
Fuzzy matching
Use the same fuzzy matching algorithm for hotwords as for the rest of the search.
As hotwords replace the entire search results, they are rather agressive. Mutliple solutions to fix this could be chosen:
Only match hotwords if their fuzzy matched score is above a certain value
Add non-completely matched hotword results into the list of normal results. (Maybe weighted by the match percentage)
This might reduce performance by a lot and/or be confusing
The fuzzy matching approach feels like the most generic, which is nice, especially to add new hotwords.
However, it might be confusing for users and its not quite as fast, as just typing a single letter.
The text was updated successfully, but these errors were encountered:
As a poweruser of Algernon, I want to be able to use shortened versions of Hotwords in order to work faster by typing less.
Possible implementations:
Acronyms for hotwords
use
b
forbrowse
,h
forhelp
, etc.-> This is more to memorize, as some hotword acronyms might overlap if we just choose the first letter. This might also require changes in the future if more hotwords are added.
Fuzzy matching
Use the same fuzzy matching algorithm for hotwords as for the rest of the search.
As hotwords replace the entire search results, they are rather agressive. Mutliple solutions to fix this could be chosen:
The fuzzy matching approach feels like the most generic, which is nice, especially to add new hotwords.
However, it might be confusing for users and its not quite as fast, as just typing a single letter.
The text was updated successfully, but these errors were encountered: