基于语义的文档关键词提取方法  

Semantic-based keyword extraction method for document

作　　者：姜芳[1] 李国和[1] 岳翔 

机构地区：[1]中国石油大学(北京)地球物理与信息工程学院油气数据挖掘北京市重点实验室,北京102249 [2]中海油研究总院信息数据中心,北京100029

出　　处：《计算机应用研究》2015年第1期142-145,共4页Application Research of Computers

基　　金：国家"863"计划资助项目(2009AA062802);国家自然科学基金资助项目(60473125);中国石油(CNPC)石油科技中青年创新基金资助项目(05E7013);国家重大专项子课题(G5800-08-ZS-WX)

摘　　要：以语义为基础实现文档关键词提取是提高自动提取准确度的有效途径。以中文文档为处理对象,通过《同义词词林》计算词语间语义距离,对词语进行密度聚类,得到主题相关类。Document keywords extraction on the basis of semantic was an effective way to improve the accuracy of automatic extraction. This paper regarded Chinese document as processing object, calculated the semantic distances between words through the synonyms dictionary. Then, through density clustering of the words, it got theme related classes. Finally, it regar- ded the headwords selected from topic related classes as keywords. Statistical experiment and scale experiment prove that the semantic-based keyword extraction method for document has higher accuracy, recall rate and the extracted keywords have high- er related degrees to the topic.

关 键 词：语义距离 密度聚类 关键词提取 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]