Error analysis of Chinese text segmentation using statistical approach

C.C. Yang, K.W. Li
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引用次数: 7

Abstract

The Chinese text segmentation is important for the indexing of Chinese documents, which has significant impact on the performance of Chinese information retrieval. The statistical approach overcomes the limitations of the dictionary based approach. The statistical approach is developed by utilizing the statistical information about the association of adjacent characters in Chinese text collected from the Chinese corpus. Both known words and unknown words can be segmented by the statistical approach. However, errors may occur due to the limitation of the corpus. In this work, we have conducted the error analysis of two Chinese text segmentation techniques using statistical approach, namely, boundary detection and heuristic method. Such error analysis is useful for the future development of the automatic text segmentation of Chinese text or other text in oriental languages. It is also helpful to understand the impact of these errors on the information retrieval system in digital libraries.
基于统计方法的中文文本分词误差分析
摘要中文文本分词是中文文献索引的重要组成部分,对中文信息检索的性能有着重要的影响。统计方法克服了基于字典的方法的局限性。统计方法是利用从汉语语料库中收集的汉语文本中相邻字符关联的统计信息来开发的。已知词和未知词都可以通过统计方法进行分词。然而,由于语料库的限制,可能会出现错误。在这项工作中,我们使用统计方法对两种中文文本分割技术进行了误差分析,即边界检测和启发式方法。这种错误分析对今后汉语或其他东方语言文本自动分词的发展具有重要的指导意义。同时也有助于了解这些错误对数字图书馆信息检索系统的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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