In this paper we study methods for improving the quality of automatic ex- traction of answer candidates for an ex- tremely challenging task: the automatic resolution of crossword puzzles for Italian language. Many automatic crossword puz- zle solvers are based on database system accessing previously resolved crossword puzzles. Our approach consists in query- ing the database (DB) with a search engine and converting its output into a probability score, which combines in a single scoring model, i.e., a logistic regression model, both the search engine score and statisti- cal similarity features. This improved re- trieval model greatly impacts the resolu- tion accuracy of crossword puzzles.

A Retrieval Model for Automatic Resolution of Crossword Puzzles in Italian Language

Nicosia, Massimo;Moschitti, Alessandro
2014-01-01

Abstract

In this paper we study methods for improving the quality of automatic ex- traction of answer candidates for an ex- tremely challenging task: the automatic resolution of crossword puzzles for Italian language. Many automatic crossword puz- zle solvers are based on database system accessing previously resolved crossword puzzles. Our approach consists in query- ing the database (DB) with a search engine and converting its output into a probability score, which combines in a single scoring model, i.e., a logistic regression model, both the search engine score and statisti- cal similarity features. This improved re- trieval model greatly impacts the resolu- tion accuracy of crossword puzzles.
2014
the First Italian Conference on Computational Linguistics (CLIC-it)
Italy
Pisa University Press
9788867414727
Gianni, Barlacchi; Nicosia, Massimo; Moschitti, Alessandro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/101834
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