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The application of structured learning in natural language processing

Record type: Article

We propose a structured learning approach, max-margin structure (MMS), which is targeted at natural language processing (NLP) tasks. The architecture of our approach is shown to capture structural aspects of the problem domains, leading to demonstrable performance improvements on two NLP tasks: part-of-speech tagging and statistical machine translation (SMT). We present a perceptron-based online learning algorithm to train the model and demonstrate desirable computational scaling behavior over traditional optimisation methods.

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Citation

Ni, Yizhao, Saunders, Craig, Szedmak, Sandor and Niranjan, Mahesan (2010) The application of structured learning in natural language processing Machine Translation

More information

Published date: May 2010
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 271262
URI: http://eprints.soton.ac.uk/id/eprint/271262
ISSN: 0922-6567
PURE UUID: cd3254a3-fd03-429f-9d8a-257e05212a15

Catalogue record

Date deposited: 14 Jun 2010 12:43
Last modified: 18 Jul 2017 06:45

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Contributors

Author: Yizhao Ni
Author: Craig Saunders
Author: Sandor Szedmak

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