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.
出处
《计算机应用研究》
CSCD
北大核心
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)
关键词
语义距离
密度聚类
关键词提取
semantic distance
density clustering
keyword extraction
