Mining h-Dimensional Enhanced Semantic Association Rule Based on Immune-Based Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{conf/wise/ZengTLQZDX06,
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title = "Mining h-Dimensional Enhanced Semantic Association
Rule Based on Immune-Based Gene Expression
Programming",
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author = "Tao Zeng and Changjie Tang and Yintian Liu and
Jiangtao Qiu and Mingfang Zhu and Shucheng Dai and
Yong Xiang",
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booktitle = "Proceedings of the Web Information Systems Workshops,
{WISE} 2006",
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publisher = "Springer",
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year = "2006",
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volume = "4256",
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editor = "Ling Feng and Guoren Wang and Cheng Zeng and
Ruhua Huang",
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pages = "49--60",
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series = "Lecture Notes in Computer Science",
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address = "Wuhan, China",
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month = oct # " 23-26",
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bibdate = "2006-11-28",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/wise/wise2006w.html#ZengTLQZDX06",
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keywords = "genetic algorithms, genetic programming, Gene
Expression Programming",
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ISBN = "3-540-47663-6",
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DOI = "doi:10.1007/11906070_5",
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abstract = "Rule mining is very important for data mining.
However, traditional association rule is relatively
weak in semantic representation. To address it, the
main contributions of this paper included: (1)
proposing formal concepts on h-Dimensional Enhanced
Semantic Association Rule (h-DESAR) with self-contained
logic operator; (2) proposing the h-DESAR mining method
based on Immune-based Gene Expression Programming
(ERIG); (3) presenting some novel key techniques in
ERIG. Experimental results showed that ERIG is
feasible, effective and stable.",
- }
Genetic Programming entries for
Tao Zeng
Changjie Tang
Yintian Liu
Jiangtao Qiu
Mingfang Zhu
Shucheng Dai
Yong Xiang
Citations