Pattern recognition in stock data based on a new segmentation algorithm

Zhang, Zhe, Jiang, Jian, Liu, Xiaoyan, Lau, Wing Chiu, Wang, Huaioing, Wang, Shanghan, Song, Xinzhu and Xu, Dongming (2007). Pattern recognition in stock data based on a new segmentation algorithm. In: KSEM 2007, Z. Zhang and J. Siekmann, Knowledge science, engineering and management [electronic resource] : second international conference, KSEM 2007, Melbourne, Australia, November 28-30, 2007 ; proceedings. 2nd International Conference on Knowledge Science, Engineering and Management (KSEM 2007), Melbourne, Australia, (520-525). 28-30 November, 2007.

Author Zhang, Zhe
Jiang, Jian
Liu, Xiaoyan
Lau, Wing Chiu
Wang, Huaioing
Wang, Shanghan
Song, Xinzhu
Xu, Dongming
Title of paper Pattern recognition in stock data based on a new segmentation algorithm
Conference name 2nd International Conference on Knowledge Science, Engineering and Management (KSEM 2007)
Conference location Melbourne, Australia
Conference dates 28-30 November, 2007
Proceedings title Knowledge science, engineering and management [electronic resource] : second international conference, KSEM 2007, Melbourne, Australia, November 28-30, 2007 ; proceedings   Check publisher's open access policy
Journal name Knowledge Science, Engineering and Management   Check publisher's open access policy
Place of Publication Berlin Heidelberg
Publisher Springer-Verlag
Publication Year 2007
Year available 2007
Sub-type Fully published paper
ISBN 9783540767183
3540767185
ISSN 0302-9743
Editor KSEM 2007
Z. Zhang
J. Siekmann
Volume LNAI 4798
Start page 520
End page 525
Total pages 6
Language eng
Subjects E1
0899 Other Information and Computing Sciences
0999 Other Engineering
Keyword Data mining
Pattern recogntion
Segmentation
Q-Index Code E1
Q-Index Status Confirmed Code

 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Google Scholar Search Google Scholar
Created: Wed, 14 May 2008, 22:00:08 EST by Karen Morgan on behalf of Faculty of Business, Economics & Law