Study on Topic Evolution based on Text Mining

被引：1
|
作者：
Wang, Jinlong [1 ]
Geng, Xueyu [2 ]
Gao, Ke [1 ]
Li, Lan [1 ]
机构：
[1] Qingdao Technol Univ, Sch Comp Engn, Qingdao 266033, Peoples R China
[2] Qingdao Technol Univ, Sch Civil Engn, Qingdao 266033, Peoples R China
来源：
FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 2, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/FSKD.2008.417
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the development of digital library technology, there are a variety of digital literatures in our life. It is very important to analyze these text for understanding topic evolution. And it is very valuable for the research work and helpful for researchers. This paper investigates this problem, and tries to use text mining technology for studying it. First, we summarize the related works, indicate their weakness, then propose the method for this problem, and present new framework and steps for this problem. Finally, the paper is summarized and some future works are also pointed out.
引用
收藏
页码：509 / +
页数：3
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