DocumentCode :
2449011
Title :
Research Challenges and Solutions for the Knowledge Overload with Data Mining
Author :
Li, Xingsen ; Zhang, Lingling ; Zhu, Zhengxiang ; Shi, Yong
Author_Institution :
Manage. Sch., Zhejiang Univ., Ningbo, China
fYear :
2009
fDate :
25-26 April 2009
Firstpage :
237
Lastpage :
240
Abstract :
The rapid development of data technology, as exemplified by data mining and Internet growth, creates a large information overload and forthcoming knowledge overload. Data mining discovers a large mount of knowledge, but not all of the knowledge is useful. Meanwhile the useful knowledge will also become un-useful as time goes by. How to manage this kind of knowledge is an urgent problem for data mining applications. A new research field called Intelligent knowledge (IK) is put forward and we try to explain the needs for coining the term as a subdiscipline of BI for systematic studies on knowledge application related theories, as well as the design of intelligent knowledge management systems (IKMS). Main topics are discussed to demonstrate why we consider IK to be a subject worthy of study and, at the same time, to establish a starting point for the further research.
Keywords :
Internet; data mining; knowledge management; Internet; data mining; intelligent knowledge management system; knowledge overload; Bismuth; Conference management; Data mining; Electronic mail; Engineering management; Humans; Knowledge management; Proposals; Research and development management; Technology management; BI; Intelligent knowledge(IK); data mining; knowledge management platform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, 2009. JCAI '09. International Joint Conference on
Conference_Location :
Hainan Island
Print_ISBN :
978-0-7695-3615-6
Type :
conf
DOI :
10.1109/JCAI.2009.137
Filename :
5158983
Link To Document :
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