Design and Development of Curious Worth Putrefaction Based on Absorbing Manuscript Recommender Procedure

Design and Development of Curious Worth Putrefaction Based on Absorbing Manuscript Recommender Procedure

  IJRES-book-cover  International Journal of Recent Engineering Science (IJRES)          
  
© 2019 by IJRES Journal
Volume-6 Issue-5
Year of Publication : 2019
Authors : Dr. S. Ravichandran, Dr. N. Jeyakumar
DOI :    10.14445/23497157/IJRES-V6I5P104

Citation 

MLA Style :Dr. S. Ravichandran, Dr. N. Jeyakumar "Design and Development of Curious Worth Putrefaction Based on Absorbing Manuscript Recommender Procedure" International Journal of Recent Engineering Science 6.5(2019):22-27. 

APA Style :Dr. S. Ravichandran, Dr. N. Jeyakumar, Design and Development of Curious Worth Putrefaction Based on Absorbing Manuscript Recommender Procedure. International Journal of Recent Engineering Science, 6(5),22-27.

Abstract
Research on the E-learning process has developed day today for the web-based educational system. To make the system even more beneficial and adaptive to the student needs, many interoperable and information retrieval services are in the existing system. Especially in the Elearning process, the data are aligned from different domain representation. The proposed technology, Singular Value Decomposition (SVD) Recommender System, summarizes the complex Matrix to find the singular value of Eigenvalues and Eigenvectors. The SVD has U, V, and S matrices, and they are known as the Orthogonal Matrix (U & V) and Diagonal Matrix (S), respectively, to decompose into single values of Eigenvalues and Eigenvectors. The diagonal Matrix consists of r, where r is the Matrix`s rank, and it has nonzero entries. This system is a factorization technique for producing a low rank of an input matrix to find the singular value. So the SVD enhances real-life classroom teaching, increasing the learning effectiveness to answer the various drawbacks of the web-based education system.

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Keywords
SVD, E-learning process, TEL, neural network, fuzzy system, and NFPR.