A probabilistic approach to solving crossword puzzles

Artificial Intelligence

Volumn 134, Issue 1-2, 2002, Pages 23-55

  Littman, Michael L ^a   Keim, Greg A ^b   Shazeer, Noam ^c  

^a AT AND T LABS RESEARCH   (United States)

^b Farfield Language Technologies   (United States)

^c GOOGLE INC   (United States)

Author keywords

Crossword puzzles; Information retrieval; Loopy belief propagation; Posterior probability; Probabilistic constraint satisfaction; Probabilistic reasoning

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONSTRAINT THEORY; INFORMATION RETRIEVAL; LEARNING SYSTEMS; PROBABILISTIC LOGICS; PROBABILITY;

COMPUTER GAMES; CROSSWORD PUZZLES;

PROBLEM SOLVING;

EID: 0036147770     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0004-3702(01)00114-X     Document Type: Article

References (24)

1. Statistical methods and linguistics
2. Indexing by latent semantic analysis
3. Search lessons learned from crossword puzzles
4. A formal basis for the heuristic determination of minimum cost paths
5. Real life information retrieval: A study of user queries on the web
6. Proverb: The probabilistic cruciverbalist
7. A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge
8. Review: Computer language games
9. Constraint satisfaction
10. Consistency in networks of relations
11. Turbo decoding as an instance of Pearl's 'belief propagation' algorithm
12. Introduction to WordNet: An one-line lexical database
13. On the hardness of approximate reasoning
14. Valued constraint satisfaction problems: Hard and easy problems
15. Solving crossword puzzles as probabilistic constraint satisfaction
16. Analysis of a very large AltaVista query log