[net.ai] Spelling Correctors = Geography test correctors?

pazzani%AEROSPACE@sri-unix.UUCP (06/27/84)

From:  Michael Pazzani <pazzani@AEROSPACE>


Ignoring philosophical issues (after all, this is AILIST not a bad remake
of "My Dinner With Andre")  I don't feel that the spelling correctors or
the geography test correctors are really that intelligent.  The geography
corrector seems to be very similar to the programs which grade SAT tests.
Surely, one wouldn't want to call a SAT test correcting program AI
even though it does a better and faster job than I would.

I think its more important to discuss how to make these programs smarter.
What would it take to have a spelling corrector find the intended word
instead of all of the possibilities?  A while ago, I worked on a program
to do word sense selection.  I wrote a spelling corrector for that
program which treated a misspelled word as new word whose senses were
the senses of all the possible corrections.  It worked well when
things like part of speech or selectional restrictions could
disambiguate.  How could one make this program smarter?  Is it possible
to try the "closer" possibilities first?  Can you propagate the part of
speech or semantic constraints into the search for possibilities?  How
would one store a large dictionary so it is efficient to find nouns,
which are vehicles which look like "planh"?  How can you detect a
spelling error if the mistake is another word?  (e.g. "I just typed
rm *.  Can you restore my flies from backup tape?)  How do people
do this anyway?