1. Solving Crossword Puzzles with AI:
a look at Proverb

2. 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

3. Goal: So how does it work?
Maximize the number of answers in the crossword puzzle that are the same as the solution.
So how does it work?

4. 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

5. 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

6. 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

7. Clue: Farrow of “Peyton Place” (answer: Mia) Confidence score = 1.0
– tom
– kip
– peg
– ray

8. 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

10. Grid Filling Probabilistic Constraint Satisfaction Problem
Each box is represented as a variable
Must maximize the correct solutions
Limitations:
confused by creativity in clues
only solves American puzzles