Constructing Knowledge Taxonomy from E-learning Portal for higher Learning Institution
Subashka Ramesh1, Aubhro Manna2, Naveen Bakshi3, Neil Thakkar4, Anurag Tiwari5
1Naveen Bakshi, Department of Computer Science & Engineering, SRM Institute Of Science & Technology, Chennai (Tamil Nadu), India.
2Aubhropratim Manna, Department of Computer Science & Engineering, SRM Institute Of Science & Technology, Chennai (Tamil Nadu), India.
3Neil Thakkar, Department of Computer Science & Engineering, SRM Institute Of Science & Technology, Chennai (Tamil Nadu), India.
4Anurag Tiwari, Department of Computer Science & Engineering, SRM Institute Of Science & Technology, Chennai (Tamil Nadu), India.
5Subashka Ramesh, Department of Computer Science & Engineering, SRM Institute of Science & Technology, Chennai (Tamil Nadu), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 1511-1514 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6334048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Electronic Educational Technology additionally called E-Learning entrance are being utilized more by school, universities, colleges and even individual teacher so as to manufacture a learning environment through Knowledge Sharing. Learning organizations gather enormous measure of data which ought to smother information the executives and information duplication adequately. For this reason, information engineering should offer a methodical technique to reuse and share the current information. This paper consequently builds Taxonomy from a lot of catchphrases for information sharing, reuse and information seek in which the developed scientific categorization ought to be free from other information arrangement. An arrangement technique utilized in developing scientific categorization is Bayesian Rose Tree and K-mean closest neighbor classifier, with the goal that the quantity of discrete qualities will build the execution of information mining model as far as order exactness. The created ordered technique and scientific categorization can be connected in reality information for effective information seek.
Keywords: Taxonomy, E-Learning, Data management, Knowledge Sharing, Data Classification
Scope of the Article: Classification