计算机工程2011，Vol.37Issue(16)：206-208,211,4.DOI:10.3969/j.issn.1000-3428.2011.16.070
基于最大熵的汉语短语结构识别方法
Recognition Method of Chinese Phrase Structure Based on Maximum Entropy
摘要
Abstract
To improve the computer's processing capacity on Chinese information, and do better shallow parsing, this paper presents a recognition method of Chinese phrase structure based on Maximum Entropy(ME). The Mutual Information(MI) among the phrases is proposed to achieve boundary prediction of the sentences structure, and the ME model is used to set up atomic and composite templates, selects more effective features for constituting the final feature set. The identification of phrase structure is completed by using the ME method, and good precision and recall are proved in the ME model based on MI by the practical experiment.关键词
浅层句法分析/互信息/边界预测/最大熵模型/特征选择Key words
shallow parsing/Mutual information(MI)/boundary prediction/Maximum Entropy(ME) model/feature selection分类
信息技术与安全科学引用本文复制引用
霍亚格,黄广君..基于最大熵的汉语短语结构识别方法[J].计算机工程,2011,37(16):206-208,211,4.基金项目
河南省科技攻关计划基金资助项目(102102210159) （102102210159）
