摘要
本文扩展和改进了现有的词语间依存关系定量识别算法,充分考虑词项概率分布的影响;明确区分词项之间的搭配关系、并列关系和从属关系,针对它们不同的特点,提出不同的识别算法;提出字串匹配模型;充分考虑两个词项之间相互位置的离散分布和距离的影响、以及它们的概率分布特性,提出词项间的依存强度模型,并据此构建词语间依存关系树;提出更新策略,对已经建好的依存关系树进行裁剪,并挖掘出潜在的依存关系。应用实验结果表明,本文提出的算法可以有效地识别出词语间的依存关系。
In order to identify the dependent relationship between words based on statistics efficiently and accurately, this paper has rectified part of the shortcomings of present algorithms by making the best of the distribution characteristic between words, distinguishing the collocation, coordinate and affiliation relationship between words, identifying them respectively by different strategies, presenting a new module of matching between strings and a new module of dependent intensity between words, constructing the tree of dependent relationship, pruning the constructed tree of dependent relationship and identifying some latent dependent relationship. The experiment confirmed that, the new algorithm can identify the dependent relationship between words very accurately.
出处
《中文信息学报》
CSCD
北大核心
2005年第4期31-38,共8页
Journal of Chinese Information Processing
基金
国家自然科学基金资助项目(60173027)
关键词
计算机应用
中文信息处理
词语搭配
依存关系
定量识别
computer application
Chinese information processing
collocation
dependent relationship
quantificational identification
