IJSTR

International Journal of Scientific & Technology Research

IJSTR@Facebook IJSTR@Twitter IJSTR@Linkedin
Home About Us Scope Editorial Board Blog/Latest News Contact Us
CALL FOR PAPERS
AUTHORS
DOWNLOADS
CONTACT
QR CODE
IJSTR-QR Code

IJSTR >> Volume 3- Issue 3, March 2014 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A Data Mining Process In An Indigenous Knowledge Ethno Medicinal Database

[Full Text]

 

AUTHOR(S)

Audrey Masizana, Gobusamang Oscar, Harriet Okatch, Barbara N. Ngwenya, Keitseng N. Monyatsi, Mbaki Muzila, Kerstin Andrae-Marobela

 

KEYWORDS

Index Terms: Apriori, Association, Confidence, Data Mining, Indigenous Knowledge Systems, Medicinal Plants, Support, Weka.

 

ABSTRACT

Abstract: Botswana is a landlocked country with diverse ethnic groups amounting to a population of around 2 million. Batswana like all the other African nations have a strong sense of culture which is expressed and strongly felt through the language, Setswana, traditional food, traditional healing and the music which form part of various indigenous knowledge systems (IKS). However, the way indigenous knowledge is or should be documented properly is subject of intense debate. Hence research projects are coming up with various methods and tools to contribute to the documentation. The Ethnosurvey Research project at University of Botswana's Centre for Scientific Research Indigenous Knowledge and Innovation (CesrIKi) set out to contribute to IKS documentation by collecting and documenting the country's traditional medicinal plants in Botswana. This paper presents the findings of conducting a data mining process on the collected data to uncover patterns and trends emerging from the data through a data mining technique.

 

REFERENCES

[1]. J. Hays, “Learning indigenous knowledge systems”, University of Tromsø, Retrieved June 11, 2011, Available: http://rwl5.uwc.ac.za/usrfiles/users/99062813/documents/Hays_Jennifer_367.doc, 2004

[2]. S.K. Sukula, “Developing indigenous knowledge databases in India”, [Online journal], Vol 24, No. 1, pg. 83-93. Retrieved September 02, 2012, Available: http://www.emeraldinsight.com. Emerald Group Publishing Limited. India, 2006

[3]. I. Hedberg and F. Staugård, “Traditional Medicine in Botswana”, Ipeleng Publishers, Botswana, 1989

[4]. M. Ishtiaq, W. Hanif, M.A. Khan, M. Ashraf, and A.M. Butt, “An ethno medicinal survey and documentation of important medicinal folklore food phytonims of flora of Samahni valley”, Laboratory of Ethno botany and Plant Taxonomy, Quaid-e-Azam University, Islamabad, 2007

[5]. A. Ribeiro, M. Romeiras, J. Tavares and M. Faria, “Ethno botanical survey in Canhane village, District of Massingir, Mozambique”, medicinal plants and traditional knowledge, Availbable: http://www.ethnobiomed.com/content/6/1/33, 03/12/2010

[6]. P. Pillay, V.J. Maharaj and P.J. Smith, “Investigating South African plants as a source of new antimalarial drugs”, 2008 Oct 28; 119(3):438-54, Epub, 2008

[7]. H. Yineger, D. Yewhalaw and D. Teketay, “Ethno medicinal plant knowledge and practice of the Oromo ethnic group in southwestern Ethiopia”, J Ethnobiol Ethno med, Ethopia, 2008

[8]. M. Baerts and J. Lehmann, “Prelude Medicinal Plants Database”, Université catholique de Louvain, Belgium, 1996

[9]. T. Leslie, “The healing power of rain forests plants”, Retrieved April 15, 2011. Available: http://www.amazon.co.uk/Healing-Power-Rainforest-Herbs-Understanding, 2005

[10]. P. Swaroop and B. Golden, “Data Mining Introduction and a Health Care Application”, Robert H Smith School of Business, University of Maryland, 2009

[11]. J. Han, M. Kamber and J. Pei, “Data Mining Concepts and Techniques (3rd Ed.) Chapter 8”, University of Illinois, Illinois, 2010

[12]. Z. Tang and J. MacLennan, “Data Mining with SQL Server 2005”, Wiley Publishing Inc. Indianapolis, USA, 2005

[13]. S. Ha and S. Joo, “A Hybrid Data Mining Method for the Medical Classification of Chest Pain”, World Academy of Science Engineering and Technology, 2010

[14]. U. Abdullah, J. Ahmad and A. Ahmed, “Analysis of effectiveness of apriori algorithm in medical billing data mining”, Emerging Technologies, Islamabad, 2008

[15]. I. Ullah, “Data Mining Algorithms And Medical Sciences”, International Journal of Computer Science and Information Technology (IJCSIT), Vol 2, No 6, Dec. 2010

[16]. S. Stilou, P. Bamidis, N. Maglaveras and C. Pappas, “Mining association rules from clinical databases, an intelligent diagnostic process in healthcare”, The Medical School, Aristotelian University, Greece, 2001

[17]. E. Frank, M. Hall, G. Holmes, R. Kirkby, B. Pfahringer, I. Witten and L. Trigg, “A Machine Learning Workbench for Data Mining”, Data Mining and Knowledge Discovery Handbook, Springer US, USA, 2010