I will echo the opinion of others in this and say that in my experience fuzzy matching based on string distance metrics is a better approach in most cases I can

I will echo the opinion of others in this and say that in my experience fuzzy matching based on string distance metrics is a better approach in most cases I can think of. I do search related stuff and we use phonetic algorithms for names (in a rather interesting way as well which I haven't seen employed elsewhere) and will occasionally get reports or inquiries of weird unexpected matches, or questions about small typos not producing any of the expected results. I feel these approaches maybe were a better fit for a time where talking was absolutely the main means of communications, but in an era where people communicate more and more by typing things into their phones, any input is frequently a) copied over instead of transcribed or b) first seen written and then typed out by the user, on a small touchscreen keyboard with 1 to 2 typos of letters close to the actual intended letter. I wonder is there such an approach that takes this key distance into account? (ie. in a search for Nock results containing Nick should be higher than Neck)