COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics

Dion Detterer; Paul H Kwan

doi:10.1007/978-3-642-28320-8_31

COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics

Dion Detterer
, Paul H Kwan (Editor)

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research

1 Citation (Scopus)

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.

Original language	English
Title of host publication	New Frontiers in Applied Data Mining
Editors	Longbing Cao, Joshua Zhexue Huang, James Bailey, Yun Sing Koh, Jun Luo
Place of Publication	Heidelberg, Germany
Publisher	Springer
Pages	361-371
Edition	1
ISBN (Print)	9783642283208, 9783642283192
DOIs	https://doi.org/10.1007/978-3-642-28320-8_31
Publication status	Published - 2012

Publication series

Name	Lecture Notes in Artificial Intelligence
Number	7104
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Neural, Evolutionary and Fuzzy Computation
Pattern Recognition and Data Mining
Traditional Chinese Medicine and Treatments

Access to Document

10.1007/978-3-642-28320-8_31

https://hdl.handle.net/1959.11/12335

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title = "COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics",

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.",

keywords = "Neural, Evolutionary and Fuzzy Computation, Pattern Recognition and Data Mining, Traditional Chinese Medicine and Treatments",

author = "Dion Detterer and Kwan, \{Paul H\}",

year = "2012",

doi = "10.1007/978-3-642-28320-8\_31",

language = "English",

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series = "Lecture Notes in Artificial Intelligence",

publisher = "Springer",

number = "7104",

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editor = "Longbing Cao and \{Zhexue Huang\}, Joshua and James Bailey and \{Sing Koh\}, Yun and Jun Luo",

booktitle = "New Frontiers in Applied Data Mining",

edition = "1",

}

Detterer, D & Kwan, PH (ed.) 2012, COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics. in L Cao, J Zhexue Huang, J Bailey, Y Sing Koh & J Luo (eds), New Frontiers in Applied Data Mining. 1 edn, Lecture Notes in Artificial Intelligence, no. 7104, Springer, Heidelberg, Germany, pp. 361-371. https://doi.org/10.1007/978-3-642-28320-8_31

COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics. / Detterer, Dion; Kwan, Paul H (Editor).
New Frontiers in Applied Data Mining. ed. / Longbing Cao; Joshua Zhexue Huang; James Bailey; Yun Sing Koh; Jun Luo. 1. ed. Heidelberg, Germany: Springer, 2012. p. 361-371 (Lecture Notes in Artificial Intelligence; No. 7104).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research

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T1 - COW

T2 - A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics

AU - Detterer, Dion

A2 - Kwan, Paul H

A2 - Cao, Longbing

A2 - Zhexue Huang, Joshua

A2 - Bailey, James

A2 - Sing Koh, Yun

A2 - Luo, Jun

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

KW - Neural, Evolutionary and Fuzzy Computation

KW - Pattern Recognition and Data Mining

KW - Traditional Chinese Medicine and Treatments

UR - http://trove.nla.gov.au/work/163564897

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DO - 10.1007/978-3-642-28320-8_31

M3 - Chapter

SN - 9783642283208

SN - 9783642283192

T3 - Lecture Notes in Artificial Intelligence

SP - 361

EP - 371

BT - New Frontiers in Applied Data Mining

PB - Springer

CY - Heidelberg, Germany

ER -

COW: A Co-evolving Memetic Wrapper for Herb-Herb Interaction Analysis in TCM Informatics

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Keywords

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