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Ni, Yizhao, Saunders, Craig, Szedmak, Sandor and Niranjan, Mahesan (2009) STRUCTURE LEARNING FOR NATURAL LANGUAGE PROCESSING At IEEE Workshops on Machine Learning for Signal Processing, 2009, France. 02 - 04 Sep 2009.

Record type: Conference or Workshop Item (Paper)


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.

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Published date: 2009
Additional Information: Event Dates: Sep 2, 2009 - Sep 4, 2009
Venue - Dates: IEEE Workshops on Machine Learning for Signal Processing, 2009, France, 2009-09-02 - 2009-09-04
Organisations: Southampton Wireless Group


Local EPrints ID: 270915
PURE UUID: 8a63cc73-379a-4ca9-a9b4-9f9fcdaa41b3

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Date deposited: 23 Apr 2010 10:51
Last modified: 18 Jul 2017 06:49

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

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