Automatic extraction of keywords from abstracts

被引：0
|
作者：
HaCohen-Kerner, Y [1 ]
机构：
[1] Jerusalem Coll Technol Machon Lev, Dept Comp Sci, IL-91160 Jerusalem, Israel
来源：
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS | 2003年 / 2773卷
关键词：
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：
The rapid increasing of online information is hard to handle. Summaries such as abstracts help us to reduce this problem. Keywords, which can be regarded as very short summaries, may help even more. Filtering documents by using keywords may save precious time while searching. However, most of the documents do not include keywords. In this paper we present a model that extracts keywords from abstracts and titles. This model has been implemented in a prototype system. We have tested our model on a set of abstracts of Academic papers containing keywords composed by their authors. Results show that keywords extracted from abstracts and titles may be a primary tool for researchers.
引用
收藏
页码：843 / 849
页数：7
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