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Semi-Markov models for sequence segmentation

Shi, Qinfeng; Altun, Yasemin; Smola, Alexander; Vishwanathan, S


In this paper, we study the problem of automatically segmenting written text into paragraphs. This is inherently a sequence labeling problem, however, previous approaches ignore this dependency. We propose a novel approach for automatic paragraph segmentation, namely training Semi-Markov models discriminatively using a Max-Margin method. This method allows us to model the sequential nature of the problem and to incorporate features of a whole paragraph, such as paragraph coherence which cannot...[Show more]

CollectionsANU Research Publications
Date published: 2007
Type: Conference paper
Source: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2007)


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