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UNSUPERVISED LEARNING USING GLOBAL FEATURES, INCLUDING FOR LOG-LINEAR MODEL WORD SEGMENTATION
UNSUPERVISED LEARNING USING GLOBAL FEATURES, INCLUDING FOR LOG-LINEAR MODEL WORD SEGMENTATION
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机译:使用全球功能进行无监督的学习,包括对数线性模型词的分段
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摘要
Described is a technology for performing unsupervised learning using global features extracted from unlabeled examples. The unsupervised learning process may be used to train a log-linear model, such as for use in morphological segmentation of words. For example, segmentations of the examples are sampled based upon the global features to produce a segmented corpus and log-linear model, which are then iteratively reprocessed to produce a final segmented corpus and a log-linear model.
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