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Solving Crossword Puzzles with AI:
a look at Proverb
What is Proverb?
Proverb was developed in 1999 to solve crosswords puzzles
Works on American puzzles Cannot beat expert humans Solves a puzzle in 15 minutes Gets over 93% of words correct
Goal:
Maximize the number of answers in the crossword puzzle that are the same as the solution.
So how does it work?
Searching…
Different searches performed depending on the category: abbr, synonym, kind of, pop culture, geography, literature, film…
Two stage architecture:1. Specific modules that generate candidate
answers
2. Combines results from the modules
Kinds of Modules
Database: movie, music, geography, literary, synonyms, etc
Syntactic: fill-in-the-blanks, kind of Word list CWDB specific Information retrieval: encyclopedia, partial
match, etc
More about modules…
modules are given the clue and the number of letters in the target
grid constraints are ignored at this point with the exception of word length
the module returns anywhere between 0 and 10,000 possible answers
each one has a weighted likelihood or probability that it is the correct solution
each module also returns a value that represents its confidence that the answer is part of its list
Clue: Farrow of “Peyton Place” (answer: Mia)
Confidence score = 1.00.909091 – mia0.010101 – tom0.010101 – kip0.010101 – kip0.010101 – peg0.010101 – ray
Training the modules…
30 modules were evaluated with test data that consisted of 5374 clues
Measures of performance: How often the correct answer was included in the
candidate list The average length of the candidate list The number of times that the correct answer
appeared as the #1 candidate Percentage of clues that the module guessed at
Grid Filling
Probabilistic Constraint Satisfaction ProblemEach box is represented as a variableMust maximize the correct solutions
Limitations:confused by creativity in clues
only solves American puzzles