loading...
A Human-Friendly MAS for Mining Stock Data
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI-IATW.2006.122006 IEEE/WIC/ACM International Confe ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Jiarui Ni, University of Technology, Sydney, Australia
Chengqi Zhang, University of Technology, Sydney, Australia
Mining stock data can be beneficial to the participants and researchers in the stock market. However, it is very difficult for a normal trader or researcher to apply data mining techniques to the data on his own due to the complexity involved in the whole data mining process. In this paper, we present a multi-agent system that can help users easily deal with their data mining jobs on stock data. This system guides users to specify their mining tasks by simply specifying the data sets to be mined and selecting pre-defined and/or user-added data mining agents. This approach offers normal traders a practical and flexible solution to mining stock data.
Citation:
Jiarui Ni, Chengqi Zhang, "A Human-Friendly MAS for Mining Stock Data," wi-iatw, pp.19-22, 2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2006
Usage of this product signifies your acceptance of the Terms of Use.