Open AccessWhat crossword puzzles teach us about information
Author(s) -
Efron Miles
Publication year - 2007
Publication title -
proceedings of the american society for information science and technology
Language(s) - English
Resource type - Journals
eISSN - 1550-8390
pISSN - 0044-7870
DOI - 10.1002/meet.1450440213
Subject(s) - computer science , context (archaeology) , conditional probability , artificial intelligence , natural language processing , mathematical economics , mathematics , statistics , paleontology , biology
Abstract This paper studies crossword puzzles as a vehicle for analyzing information in a rigorous yet meaningful fashion. The paper asks, how does information operate in the context of crossword puzzles? A model is proposed that quantifies the difficulty of a puzzle P with respect to its clues. Given a clue‐answer pair (c,a), we model the difficulty of guessing a based on c using the conditional probability Pr(a | c); easier mappings should enjoy a higher conditional probability. The model is tested on a corpus of puzzles taken from The New York Times. Additionally, we discuss how the notion of information implicit in our model relates to more easily quantifiable types of information that figure into crossword puzzles.