Name
Abstract | ||
|---|---|---|
We attacked the problem of solving crossword puzzlesby computer: Given a set of clues and a crosswordgrid, try to maximize the number of words correctlyfilled in. Proverb, the probabilistic cruciverbalist,separates the problem into two, more familiarsubproblems: candidate generation and grid filling. Incandidate generation, each clue is treated as a type ofquery to an information retrieval system, and relevantwords of the correct length are returned along withconfidence scores. In grid ... |
Year | Venue | Keywords |
|---|---|---|
1999 | National Conference on Artificial Intelligence | puzzle grid,candidate generation,candidate-generation process,overall confidence score,confidence score,candidate word,belief network inference,crossword puzzle,crossword grid,complete puzzle,information retrieval system |
Field | DocType | ISBN |
Confidence score,Constraint satisfaction,Inference,Computer science,Bayesian network,Artificial intelligence,Probabilistic logic,Machine learning,Grid | Conference | 0-262-51106-1 |
Citations | PageRank | References |
4 | 1.60 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael L. Littman | 1 | 9798 | 961.84 |
| Greg A. Keim | 2 | 87 | 12.95 |
| Noam Shazeer | 3 | 1089 | 43.70 |