Review 7

From: Tyler Robison (trobison_at_cs.washington.edu)
Date: Mon Dec 08 2003 - 09:52:39 PST

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    PROVERB: The Probabilistic Cruciverbalist
    Greg A Keim, Noam M Shazeer, Michael L Littman

    Summary:
            The authors present a system that solves cross-word puzzles by
    having 'expert modules' for various knowledge domains guess words based on
    given clues.

    Important Ideas:
            The most interesting part of this in my mind is trying to match
    words to the clues given, a problem which seems like it would be very
    difficult for a computer, but with which they have had significant
    success. To do this, they use several expert modules which return lists
    of possibilities along with weights indicating the likelihood.
            One thing that struck me is the thorough way in which they
    evaluated the system. The problems they tried to solve weren't conceived
    for the purpose of the experiment; they were real cross-word puzzles, and
    so it is easy to compare the performance of the system against actual
    people. In addition, they performed tests after removing certain modules
    to see the dependence of the system on them. Overall, it seemed like they
    did a good job of evaluating the system.

    Flaws:
            I did like this paper, but one flaw stands out nonetheless: it is
    an application of various techniques, and not really a general tool
    itself; it doesn't appear to have much use outside of cross-word puzzles.
    Despite this, it does show-off the potential of AI by being very
    successful at a problem that seems very 'human' in nature, and so seems
    worthwhile.

    Research Questions:
            Since much of the problem involves figuring out clues, it could be
    interesting seeing similar techniques applied other problems that require
    guessing the answer to some clue, such as riddles, for example. Of
    course, in the cross-word puzzle problem, they have the benefit of knowing
    the length (and possibly some letters) of the answer, so this may not work
    at all.
            One could also think of expanding & improving the technique to the
    point that the program is on par with human masters. Since this isn't a
    well researched area, there is certainly room for improvement.


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