Automatic Keyphrase Extraction from Medical Documents

被引：0
作者：
Sarkar, Kamal [1 ]
机构：
[1] Jadavpur Univ, Comp Sci & Engn Dept, Kolkata 700032, India
来源：
PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PROCEEDINGS | 2009年 / 5909卷
关键词：
Domain specific keyphrase extraction; Medical documents; Text mining; Naive Bayes;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Keyphrases provide semantic metadata that summarizes the documents and enable the reader to quickly determine whether the given article is in the reader's fields of interest. This paper presents an automatic keyphrase extraction method based on the naive Bayesian learning that exploits a number of domain-specific features to boost up the keyphrase extraction performance in medical domain. The proposed method has been compared to a popular keyphrase extraction algorithm, called Kea.
引用
收藏
页码：273 / 278
页数：6
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