基于马尔可夫链的中文分词改进算法研究

Pang Baomao, Shi Haoshan
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引用次数: 5

摘要

中文分词是中文网页数据挖掘的一项重要技术。本文通过对目前一些中文分词算法的研究,提出了一种改进的分词算法。该算法采用双向马尔可夫链更新词典,采用改进的基于词频统计的前向最大匹配方法进行分词。仿真结果表明,该算法可以快速准确地完成给定文本的分词。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Improved Algorithm for Chinese Word Segmentation Based on Markov Chain
Chinese words segmentation is an important technique for Chinese web data mining. After the research made on some Chinese word segmentation nowadays, an improved algorithm is proposed in this paper. The algorithm updates dictionary by using Two-way Markov Chain, and does word segmentation by applying an improved Forward Maximum Matching Method based on word frequency statistic. The simulation shows this algorithm can finish word segmentation for a given text quickly and accurately.
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