International Journal of Information Technology and Computer Science(IJITCS)
ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)
Published By: MECS Press
IJITCS Vol.5, No.2, Jan. 2013
Knowledge Discovery in Endangered Species Diversification
Full Text (PDF, 530KB), PP.57-65
Classification of regional territories and countries related to endangered species has been investigated by data mining techniques and graphical modeling using an extensive data set of species. We developed the graphical models (hereafter referred to as ‘ESDI’) using cosine, jaccard similarity, K Mean clustering and cliques in graph modeling for a large number of countries. Environmental variables associated with species records were identified in context of their diversification to integration with our proposed prototype. We have shown that the problem of finding the most coherent clusters is reducible to finding maximum clique. Key findings include the urge to ameliorate communication about the loss and protection of endangered species and their concerned projects. The proposed framework is presented to serves a portal to knowledge discovery. We have concluded that the proposed framework model and its associated data mining similarity measures can be useful for investigating various scientific and management oriented questions related to protection of endangered species with emphasis on collaboration among regional countries. The rationale behind the proposed approach is that the countries which have been grouped into same clique inherit a lot of argues illustrating common reasons of their struggles towards ecological safety with minimization of perils for endangered species. The development and implementation of a regional approach based on this similar grouping address the actions that could offer significant benefits in achieving their goal for ecological policies. Other critical actions at this clique level include fortifying and elevating harmonization of legal frameworks with emphasis on prevention procedural issues; awareness realizations of endangered species issues and its priority. Such actions will eventually lead towards implementation of essential plans fulfilling co-operative expertise and common endeavors.
Cite This Paper
Muhammad Naeem, Sohail Asghar,"Knowledge Discovery in Endangered Species Diversification", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.2, pp.57-65, 2013.DOI: 10.5815/ijitcs.2013.02.06
Ramsey F.P, On a problem of formal logic, [C]. Proc. London Math. Soc., 1930.
Fayyad U.M., Piatetsky-Shapiro G. P., and Smyth, From data mining to knowledge discovery: an overview, Advances in Knowledge Discovery in Data Mining[C]., AAAI Press, Menlo Park, CA, 1996, pp. 1 –34.
Manley, P.N., Zielinski, W.J., Schlesinger, M.D., Mori, S.R., 2004. Evaluation of a multiple-species approach to monitoring species at the ecoregional scale[J].. Ecological Applications 14 (1), 296e310.
Tim O’Riordan & Susanne Stoll-Kleemann, Biodiversity[J]., Sustainability and Human Communities 14 (2002).
United Nations Environmental Program (UNEP) [M]., Global Biodiversity Assesement (1995).
Dennis Pirages and Theresa DeGeest, Ecological Security 141 (2004) [M]., Studies report little on the impact of habitat loss on protozoa, nematodes, and other micro-organisms.
Paul F. Steinberg (2005): From Public Concern to Policy Effectiveness: Civic Conservation in Developing Countries[J]., Journal of International Wildlife Law & Policy, 8:4, 341-365
Brian Dennis, Patricia L. Munholland, Michael Scott, Estimation of growth and extinction parameters for endangered species[J]., Ecological Monographs, 61(2), 1991, pp. 115-143.
David R.B. Stockwell, Improving ecological niche models by data mining large environmental datasets for surrogate models[J]., Ecological Modeling 192 (2006) 188–196.
John B. Loomis, Douglas S. (1996), White, Economic benefits of rare and endangered species: summary and meta-analysis[J]., Ecological Economics 18 (1996) 197-206.
Iga Lewina, Adam Smolin´ skib, Rare and vulnerable species in the mollusc communities in the mining subsidence reservoirs of an industrial area (The Katowicka Upland, Upper Silesia, Southern Poland) [J]. Limnologica 36 (2006) 181–191.
Wong I.W., Bloom R., McNicol D.K., Fong P., Russell R., Chen X., Species at risk: Data and knowledge management within the wildspace Decision Support System[J]. Environmental Modeling & Software 22 (2007) 423-430,
Joseph Domask (2004): Science, Policy Process and Policy Ownership in Africa and The Caribbean[J]., Journal of International Wildlife Law & Policy, 7:3-4, 223-232
Glenn, C. R. 2006. "Earth's Endangered Creatures" (Online). Accessed Aug-2012 at http://earthsendangered.com.
Tan, Pang-Ning; Steinbach, Michael; Kumar, Vipin (2005), Introduction to Data Mining [M]., ISBN 0-321-32136-7.
Jaccard, Paul (1901), Étude comparative de la distribution florale dans une portion des Alpes et des Jura [M]. Bulletin de la Société Vaudoise des Sciences Naturelles 37: 547–579.
Hansen P. and Jaumard B., Cluster analysis and mathematical programming[J]., Math. Program., vol. 79, pp. 191–215, 1997.
Jessica L. Blickley and Gail L. Patricelli (2010): Impacts of Anthropogenic Noise on Wildlife: Research Priorities for the Development of Standards and Mitigation[J]., Journal of International Wildlife Law & Policy, 13:4, 274-292
Council of Europe/UNEP, Pan‐European biological and landscape diversity strategy, Invasive Alien Species[J]., Journal of International Wildlife Law & Policy, 5:3, 291-305.
Geoffrey Wandesforde-Smith , Nicholas S.J. Watts and Arielle Levine (2010): Wildlife Conservation and Protected Areas: Darwin, Marx, and Modern Science in the Search for Patterns That Connect[J]., Journal of International Wildlife Law & Policy, 13:4, 357-374