Research on Knowledge Discovery in Knowledge Base

被引：0
|
作者：
Yang Bing-ru [1 ]
Li Guang-yuan [1 ,2 ]
Liu Yong-bin [1 ,3 ]
机构：
[1] Univ Sci & Technol Beijing, Sch Informat Engn, Beijing, Peoples R China
[2] Guangxi Teachers Educ Univ, Sch Comp & Informat Engn, Nanning, Guangxi, Peoples R China
[3] Tianjin Univ Finance & Econ, Dept Informat & Comp Sci, Tianjin, Peoples R China
来源：
2011 INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND NEURAL COMPUTING (FSNC 2011), VOL VI | 2011年
关键词：
knowledge base; knowledge discovery; data mining; KDK;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Knowledge discovery in knowledge base(KDK) is a new and important direction in data mining. Its results can be used to construct large knowledge base, and it is very important for knowledge obtaining which is a bottleneck in machine learning. In this paper, we discuss some issues related with KDK, which include the theoretical frameworks for KDK, modeling of KDK, and the key techniques of KDK, that provide theoretical support and directions for the further research on KDK.
引用
收藏
页码：413 / 417
页数：5
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