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An Intelligent Content Classification Algorithm for Effective E-Learning


N. Partheeban, Dr. N. Sankar Ram
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In this paper, we propose a new content recommendation system called Intelligent Content Recommendation System for E-Learning for selecting and retrievingthe exact e-content for teaching the subject “Software Engineering” based on group discussions through the social media. In this process, we analyze the various contents pertaining to the subject Software Engineeringand select the suitable e-content for recommending to the students and industrial people such as software developers. For this purpose, we use an intelligent preprocessing technique and also propose a new classification algorithm called Intelligent Ranked Document Classification algorithm for classifying and ranking the e-contents. In addition, we use the existing New Weighted Fuzzy C-Means clustering algorithm to help the decision making system to recommend suitable contents using fuzzy rules. The main advantage of the proposed system is that it provides different types of contents which are suitable to different types of learners accurately.

N. Partheeban, Dr. N. Sankar Ram

Feature Selection, Enhanced MSVM, Weighted Fuzzy C-Means, Ranking, Clustering, Classification, Semantic Analysis.

  1. KatrienVerbert, Nikos Manouselis, Xavier Ochoa, Martin Wolpers, HendrikDrachsler, IvanaBosnic, Erik Duval, “Context-Aware Recommender Systems forLearning: A Survey and Future Challenges”, IEEE Transactions On Learning Technologies, Vol. 5, No. 4, pp. 318- 335, 2012.
  2. Mohamed Amine Chatti, Ulrik Schroeder, and Matthias Jarke, “LaaN: Convergence ofKnowledge Management and Technology-Enhanced Learning”, IEEE Transactions on Learning Technologies, Vol. 5, No. 2, pp. 177- 189, 2012.
  3. SannasiGanapathy, KanagasabaiKulothungan, SannasyMuthurajkumar, MuthusamyVijayalakshmi, PalanichamyYogesh, ArputharajKannan, “Intelligent feature selection and classification techniques for intrusion detection in networks: a survey”, EURASIP Journal on Wireless Communications and Networking, Vol. 2013, pp. 1-16, 2013.
  4. Ahmed Al-Hmouz, Jun Shen, Rami Al-Hmouz, and Jun Yan, “Modeling and Simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning”, IEEE Transactions on Learning Technologies, Vol. 5, No. 3, pp. 226- 237, 2012.
  5. Ekaterina Gilman, Ivan Sanchez Milara, Marta Cortes, and JukkaRiekki, “Towards User Support in UbiquitousLearning Systems”, IEEE Transactions on Learning Technologies, Vol. 8, No. 1, pp. 55-68, 2015.
  6. Ganapathy S, Sethukkarasi R, Yogesh P, Vijayakumar P, Kannan A, “An intelligent temporal pattern classification system using fuzzy temporal rules and particle swarm optimization”, Sadhana, Vol.39, No.2, pp. 283-302, 2014.
  7. P. Vate-u-lan.(2008). Borderless e-learning: HITS Model for Web 2.0. [Online]. Available: http://ejournals.thaicyberu.go.th/index.php/ictl/article/view/59/62.
  8. Murphy P M and Aha D W 1995 UCI Repository of Machine Learning Databases, (Machine-Readable Data Repository). Irvine, CA: Dept. Inf. Comput. Sci., University of California.
  9. SaiRamesh L, SannasiGanapathy, Bhuvaneshwari R, KanagasabaiKulothungan, V. Pandiyaraju, ArputharajKannan, “Prediction of User Interests for Providing Relevant Information Using Relevance Feedback and Re-ranking”, International Journal of Intelligent Information Technologies, Vol.11, No.4, pp. 55-71, 2015.
  10. Ganapathy S, Kulothungan K, Yogesh P, Kannan A, “A Novel Weighted Fuzzy C–Means Clustering Based on Immune Genetic Algorithm for Intrusion Detection”, Procedia Engineering, Vol. 38, pp. 1750-1757, 2012.
  11. Rodrigues J.J.P.C, SabinoF.M.R, Zhou L, “Enhancing e-learning experience with onlinesocial networks”, IET Communications, 2011, Vol. 5, No. 8, pp. 1147–1154, 2011.

Publication Details

Published in : Volume 2 | Issue 4 | July-August - 2016
Date of Publication Print ISSN Online ISSN
2016-08-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
285-289 IJSRSET162469   Technoscience Academy

Cite This Article

N. Partheeban, Dr. N. Sankar Ram, "An Intelligent Content Classification Algorithm for Effective E-Learning ", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 4, pp.285-289, July-August-2016.
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