Solving Crossword Puzzles Using Extended Potts Model

  • Kazuki Jimbo
  • Hiroya Takamura
  • Manabu Okumura
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5447)


Solving crossword puzzles by computers is a challenging task in artificial intelligence. It requires logical inference and association as well as vocabulary and common sense knowledge. For this task, we present an extension of the Potts model. This model can incorporate various clues for solving puzzles and require less computational cost compared with other existing models.


World Wide Potts Model Candidate List Random Initialization Linguistic Resource 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kazuki Jimbo
    • 1
  • Hiroya Takamura
    • 2
  • Manabu Okumura
    • 2
  1. 1.Department of Computer ScienceTokyo Institute of TechnologyJapan
  2. 2.Precision and Intelligence LaboratoryTokyo Institute of TechnologyJapan

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