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基于语义的自动文摘研究综述
引用本文:龚书,瞿有利,田盛丰.基于语义的自动文摘研究综述[J].北方交通大学学报,2009(5):126-131.
作者姓名:龚书  瞿有利  田盛丰
作者单位:北京交通大学计算机与信息技术学院,北京100044
基金项目:教育部科学技术研究重点项目(108126);国家自然科学基金资助项目(10871019/a0107)
摘    要:基于语义的自动文摘方法能解决自动文摘处理中语言复杂性问题,在克服领域局限性的同时从本质上提高文摘的质量.常用语义模型包括统计主题模型扣语义知识模型.基于语义的自动文摘是对传统文摘技术基于语义模型的扩充,在自动文摘的预处理、文档转换、文档候选片段提取和文摘生成4个基本过程中使用各种语义分析方法.

关 键 词:自然语言处理  自动文摘  语义  语义模型  本体

Review of the Research on Semantic-Based Automatic Summarization
GONG Shu,Qu Youli,TIAN Shengfeng.Review of the Research on Semantic-Based Automatic Summarization[J].Journal of Northern Jiaotong University,2009(5):126-131.
Authors:GONG Shu  Qu Youli  TIAN Shengfeng
Institution:(School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China)
Abstract:Automatic summarization is an important researching branch of natural language processing. Semantic-based automatic summarization method solved the language complexity problem, increased the generality of summarization system, while improved the quality of summary. Statistic topic model and semantic knowledge model are the two main semantic models. Semantic-based automatic summarization enlarges the traditional, summarization technology by semantic models, and using semantic analysis methods in the four basic processes of automatic summarization: preprocessing, document transferring, summarization candidate fragments extracting and summarization generating. Semanticbased automatic summarization still has a wide space to develop.
Keywords:natural language processing  automatic summarization  semantics  semantic model  ontology
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