Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12335
Title: COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics
Contributor(s): Detterer, Dion (author); Kwan, Paul H  (editor)
Publication Date: 2012
DOI: 10.1007/978-3-642-28320-8_31
Handle Link: https://hdl.handle.net/1959.11/12335
Abstract: Traditional Chinese Medicine (TCM) relies heavily on interactions between herbs within prescribed formulae. However, given the combinatorial explosion due to the vast number of herbs available for treatment, the study of herb-herb interactions by pure human analysis is impractical, with computer aided analysis computationally expensive. Thus feature selection is crucial as a pre-processing step prior to herb-herb interaction analysis. In accord with this goal, a new feature selection algorithm known as a Co-evolving Memetic Wrapper (COW) is proposed: COW takes advantage of recent developments in genetic algorithms (GAs) and meme tic algorithms (MAs). evolving appropriate feature subsets for a given domain. As part of preliminary research. COW is demonstrated to he effective in selecting herbs in the TCM insomnia dataset. Finally, possible future applications of COW are examined, both within TCM research and in broader data mining contexts.
Publication Type: Book Chapter
Source of Publication: New Frontiers in Applied Data Mining, p. 361-371
Publisher: Springer
Place of Publication: Heidelberg, Germany
ISBN: 9783642283208
9783642283192
Fields of Research (FoR) 2008: 080109 Pattern Recognition and Data Mining
110404 Traditional Chinese Medicine and Treatments
080108 Neural, Evolutionary and Fuzzy Computation
Fields of Research (FoR) 2020: 461199 Machine learning not elsewhere classified
420803 Traditional Chinese medicine and treatments
460203 Evolutionary computation
Socio-Economic Objective (SEO) 2008: 920199 Clinical Health (Organs, Diseases and Abnormal Conditions) not elsewhere classified
970108 Expanding Knowledge in the Information and Computing Sciences
890201 Application Software Packages (excl. Computer Games)
Socio-Economic Objective (SEO) 2020: 280115 Expanding knowledge in the information and computing sciences
220401 Application software packages
HERDC Category Description: B1 Chapter in a Scholarly Book
Publisher/associated links: http://trove.nla.gov.au/work/163564897
Series Name: Lecture Notes in Artificial Intelligence
Series Number : 7104
Editor: Editor(s): Longbing Cao, Joshua Zhexue Huang, James Bailey, Yun Sing Koh, Jun Luo
Appears in Collections:Book Chapter

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