Semi-Markov models for sequence segmentation
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]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2007)|
|01_Shi_Semi-Markov_models_for_2007.pdf||806.88 kB||Adobe PDF||Request a copy|
|02_Shi_Semi-Markov_models_for_2007.pdf||29.43 kB||Adobe PDF||Request a copy|
|03_Shi_Semi-Markov_models_for_2007.pdf||355.14 kB||Adobe PDF||Request a copy|
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