Dr. Lee Lam Hong

>>Dr. Lee Lam Hong
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Qualifications:
  • BCompSc (Hons)(UPM)
  • PhD (Nottingham)
 Research and Teaching Experience: 10 Years
  • years (UTAR, 2009 – 2011) (Teaching)
  • 10 year (Research Experience)
Field of Interest: 
Machine Learning, Pattern Recognition, Intelligent Systems, Text Classification, Knowledge Engineering, Data Mining
Other Relevant Information:
  1. Editor – Journal of Advances in Information Technology
  2. Reviewer – Information Sciences, Journal of Applied Sciences, International Journal of Computer Science and Information Security
Selected Publication:
  1. L. H. Lee, R. Rajkumar, L. H. Lo, C. H. Wan, D. Isa (2013), Oil and Gas Pipeline Failure Prediction System using Long Range Ultrasonic Transducers and Euclidean-Support Vector Machines Classification Approach. Expert Systems With Applications – Elsevier, 40(6): 1925-1935.
  2. Wan,   Lee, R. Rajkumar, D. Isa (2012), A Hybrid Text Classification Approach with Low Dependency on Parameter by integrating K-Nearest Neighbor and Support Vector Machine. Expert Systems With Applications – Elsevier, 39(15): 11880-11888.
  3. Lee, Wan, R. Rajkumar, D. Isa (2012), An Enhanced Support Vector Machine Classification Framework By Using Euclidean Distance Function For Text Document Categorization. Applied Intelligence – Springer, 37(1): 80-99.
  4. Lee, R. Rajkumar, D. Isa (2012), Automatic Folder Allocation System Using Bayesian – Support Vector Machines Hybrid Classification Approach. Applied Intelligence – Springer, 36(2): 295-307.
  5. L. H. Lee, D. Isa, W. O. Choo, W. Y. Chue (2012), High Relevance Keyword Extraction Facility For Bayesian Text Classification On Different Domains Of Varying Characteristic. Expert Systems With Applications – Elsevier, 39(1): 1147-1155.

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