Mining h-Dimensional Enhanced Semantic Association Rule Based on Immune-Based Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{conf/wise/ZengTLQZDX06,

• title = "Mining h-Dimensional Enhanced Semantic Association Rule Based on Immune-Based Gene Expression Programming",
• author = "Tao Zeng and Changjie Tang and Yintian Liu and Jiangtao Qiu and Mingfang Zhu and Shucheng Dai and Yong Xiang",
• booktitle = "Proceedings of the Web Information Systems Workshops, {WISE} 2006",
• publisher = "Springer",
• year = "2006",
• volume = "4256",
• editor = "Ling Feng and Guoren Wang and Cheng Zeng and Ruhua Huang",
• pages = "49--60",
• series = "Lecture Notes in Computer Science",
• address = "Wuhan, China",
• month = oct # " 23-26",
• bibdate = "2006-11-28",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/wise/wise2006w.html#ZengTLQZDX06",
• keywords = "genetic algorithms, genetic programming, Gene Expression Programming",
• ISBN = "3-540-47663-6",
• DOI = "doi:10.1007/11906070_5",
• 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