Review of Computer Engineering Research

Published by: Conscientia Beam
Online ISSN: 2410-9142
Print ISSN: 2412-4281
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No. 1

Web Pages Categorization Based on Classification & Outlier Analysis through FSVM

Pages: 19-30
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Web Pages Categorization Based on Classification & Outlier Analysis through FSVM

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Geeta R.B. , Shobha R.B. , Shashikumar G. Totad , Prasad Reddy PVGD

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  1. J. C. Platt, Sequential minimal optimization-A fast algorithm for training support vector machines, in advances in kernel methods-support vector learning. Cambridge, MA: MIT Press, 1998.
  2. D. Gomez, J. Montero, and G. Biging, "Improvements to remote sensing using fuzzy classification, graphs and accuracy statistics," Pure Appl. Geophys., vol. 165, pp. 1555-1575, 2008.
  3. E. O. Edgar, F. Robert, and G. Federico, Support vector machines: Training and applications: A.I. Memo No. 1602, C.B.C.L Paper No.144, March 1997, 2004.
  4. P. Scott and H. Lutz, "Comparing the results of support vector machines with traditional data mining algorithms, supported by Amica Life Insurance Company."
  5. W. Xiao-Hong, "Coll. of electr and inf eng, Jiangsu Univ, Zhenjiang. A possibilistic C- means clustering algorithm based on kernel methods," presented at the Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Nov 2005.
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Geeta R.B. , Shobha R.B. , Shashikumar G. Totad , Prasad Reddy PVGD (2014). Web Pages Categorization Based on Classification & Outlier Analysis through FSVM. Review of Computer Engineering Research, 1(1): 19-30. DOI:
The performance of Support Vector Machine is higher than traditional algorithms. The training process of SVM is sensitive to the outliers in the training set. Here in this Paper, a new approach called, Web Pages Categorization based on Classification and Outlier Analysis (WPC-COA), is proposed that uses a polynomial Kernel function to map web page tuples to high dimensional feature space. 


Contribution/ Originality
This study uses a new methodology which helps in mapping web page tuples with various attributes such as frequency, time spent on each page, in-degree, out-degree and level of a web page to high dimensional feature space. The paper’s primary contribution is to categorize web pages based on classification and outlier analysis using Polynomial Kernel function.

Quasi 3d Refined Simulation of Flow and Pollutant Transport in the Yangtze River

Pages: 1-18
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Quasi 3d Refined Simulation of Flow and Pollutant Transport in the Yangtze River

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Li-ren Yu

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Li-ren Yu (2014). Quasi 3d Refined Simulation of Flow and Pollutant Transport in the Yangtze River. Review of Computer Engineering Research, 1(1): 1-18. DOI:
This paper reports a quasi 3D simulation in a curved river reach of The Yangtze River near The Huangshigang City, aiming to develop a numerical tool for modeling turbulent flows and pollutant transport in complex natural waters. The depth-averaged two-equation turbulence   model, together with   and   models, were used to close quasi 3D hydrodynamic fundamental governing equations. The discretized equations were solved by advanced multi-grid iterative method under coarse and fine two-levels’ grids. The processes of plume development, caused by the side-discharge from a tributary, also have been investigated numerically. The used three turbulence models are suitable for modeling strong mixing turbulence. The   model with higher order of magnitude of transported variable   provides a possibility to increase the computational precision. Based on the developed hydrodynamic model, a CFD software, namely Q3drm1.0, was preliminarily developed. This tool focuses on the refined simulations of the steady and unsteady problems of flow and transports with the strong ability to treat different types of discharges.
Contribution/ Originality