A00-1027 syllable of the compound noun . The segmentation algorithm is effectively implemented by
C02-1148 three families of Chinese word segmentation algorithms from the recent literature .
C02-1006 Next , we applied another topic segmentation algorithm developed by Utiyama et al. (
A00-1027 section , we generalize the word segmentation algorithm based on data obtained by the
A00-2004 accuracy and speed performance of segmentation algorithms . A sample is a concatenation
C02-1006 ) . The results show that this segmentation algorithm is better than TextTiling . But
C02-1006 overall performance depends on the segmentation algorithm . We make an index file similar
A92-1013 N_prep_ADJ , V_prep_ADJ . The segmentation algorithm is very simple . If the domain
A00-1027 the built-in dictionary and the segmentation algorithm which reflects system accuracy
A00-2032 Japanese texts . Typical Japanese segmentation algorithms rely either on a lexicon and
A00-1027 are about 100,000 . Second , the segmentation algorithm is applied if the compound noun
A00-1027 million word corpus . Second , a segmentation algorithm using statistical data is proposed
A00-2004 Conclusions and future work A segmentation algorithm has two key elements , a , clustering
A00-2004 improve accuracy . 3 Algorithm Our segmentation algorithm takes a list of tokenized sentences
A00-1027 pattern has the pri - ority . 3.2 Segmentation Algorithm In this section , we generalize
C02-1148 , using a wide variety of word segmentation algorithms with word segmentation accuracies
A97-1049 segmentation . However , most segmentation algorithms are more likely to make errors
C02-1148 . Below we first describe the segmentation algorithms we used , and then discuss the
A00-1027 about 50,000 . 3 Compound Word Segmentation Algorithm 3.1 Basic Idea To simply describe
A00-2032 experimentally evaluated , nor is a general segmentation algorithm proposed . The work of Ito and
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