(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.