(March 7, 2016) A web-based machine language system solves
crossword puzzles far better than commercially-available products, and may help
machines better understand language.
Researchers have designed a web-based platform which uses
artificial neural networks to answer standard crossword clues better than
existing commercial products specifically designed for the task. The system,
which is freely available online, could help machines understand language more
effectively.
In tests against commercial crossword-solving software, the
system, designed by researchers from the UK, US and Canada, was more accurate at
answering clues that were single words (e.g. ‘culpability’ – guilt), a short
combination of words (e.g. ‘devil devotee’ – Satanist), or a longer sentence or
phrase (e.g. ‘French poet and key figure in the development of Symbolism’ –
Baudelaire). The system can also be used a ‘reverse dictionary’ in which the
user describes a concept and the system returns possible words to describe that
concept.
The researchers used the definitions contained in six
dictionaries, plus Wikipedia, to ‘train’ the system so that it could understand
words, phrases and sentences – using the definitions as a bridge between words
and sentences. Their results, published in the journal Transactions of the
Association for Computational Linguistics, suggest that a similar approach may
lead to improved output from more general language understanding and dialogue
systems and information retrieval engines in general. All of the code and data
behind the application has been made freely available for future research.