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- W2034790871 abstract "Word segmentation is the crucial first step of natural language understanding (NLU) for Chinese corpora. Our early paper presented Evaluation Selection and Adjustment (ESA), an unsupervised approach to word In this article, we present a novel non-iterative variation of ESA, comparing it with other similar methods and we get better performance. Besides that, we analyze Balancing and compare it with Standardizing, another algorithm, to solve the problem of how to evaluate the words of different lengths and compare them with each other for statistical methods of word segmentation. The experimental results show that Balancing is more effective than Standardizing for the task." @default.
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- W2034790871 date "2014-06-01" @default.
- W2034790871 modified "2023-09-26" @default.
- W2034790871 title "A novel unsupervised non-iterative approach to word segmentation" @default.
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- W2034790871 doi "https://doi.org/10.1109/icsess.2014.6933693" @default.
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