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机构地区:[1]北京工业大学计算机学院,北京100022 [2]北京语言大学信息科学学院,北京100083
出 处:《计算机研究与发展》2006年第6期1122-1128,共7页Journal of Computer Research and Development
基 金:国家自然科学基金项目(60272055);国家"八六三"高技术研究发展计划基金项目(2001AA114111);教育部科学技术研究重点基金项目(00128);教育部人文社会科学重点研究基地重大项目(02JAZJD740007)~~
摘 要:歧义切分技术是中文自动分词系统的关键技术之一·特别是在现代汉语通用分词系统(GPWS)中,允许用户动态创建词库、允许多个用户词库同时参与切分,这给歧义切分技术提出了更高的实用性要求·从大规模的真实语料库中,考察了歧义(特别是交集型歧义)的分布情况和特征;提出了一种改进的正向最大匹配歧义字段发现算法;并根据GPWS的需求,提出了一种“规则+例外”的实用消歧策略·对1亿字《人民日报》语料(约234MB)中的交集型歧义字段进行了穷尽式的抽取,并随机的对上述策略进行了开放性测试,正确率达99%·Disambiguation is one of the most important parts of segment systems in Chinese. A Chinese general-purpose word segmentation (GPWS) system demands higher capacity of disambiguation techniques particularly, because it has functions such as allowing users to create their own dictionaries dynamically and employing multiple user' s dictionaries to word segmentation. Based on inspection of the distributions and characteristics of ambiguity fragments (especially overlapping ambiguity fragments) in large-scale real corpus, an improved forward maximum match algorithm for ambiguity fragment detection, as well as a practical " rules + exceptions" disambiguation strategy, are proposed in this paper. An exhaustive extraction has been made of the overlapping ambiguity sections (about 2.4 million occurrences) from a People's Daily corpus of 100 million characters (234MB approximately), and open-ended experiments on the above strategy randomly were carried out, which achieved accuracy average of 99 %.
分 类 号:TP391.12[自动化与计算机技术—计算机应用技术]
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