STRUCTURE LEARNING FOR NATURAL LANGUAGE PROCESSING
Ni, Yizhao, Saunders, Craig, Szedmak, Sandor and Niranjan, Mahesan (2009) STRUCTURE LEARNING FOR NATURAL LANGUAGE PROCESSING. In, IEEE Workshops on Machine Learning for Signal Processing, 2009, Grenoble, France, 02 - 04 Sep 2009.
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Description/Abstract
We applied a structure learning model, Max-Margin Structure (MMS), to natural language processing (NLP) tasks, where the aim is to capture the latent relationships within the output language domain. We formulate this model as an extension of multi–class Support VectorMachine (SVM) and present a perceptron–based learning approach to solve the problem. Experiments are carried out on two related NLP tasks: part–of–speech (POS) tagging and machine translation (MT), illustrating the effectiveness of the model.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Event Dates: Sep 2, 2009 - Sep 4, 2009 |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 270915 |
| Date Deposited: | 23 Apr 2010 10:51 |
| Last Modified: | 26 Apr 2013 04:54 |
| Contributors: | Ni, Yizhao (Author) Saunders, Craig (Author) Szedmak, Sandor (Author) Niranjan, Mahesan (Author) |
| Date: | 2009 |
| Additional Information: | Event Dates: Sep 2, 2009 - Sep 4, 2009 |
| Status: | Published |
| Further Information: | Google Scholar |
| ISI Citation Count: | 0 |
| URI: | http://eprints.soton.ac.uk/id/eprint/270915 |
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