The Classification Techniques of Websites for The Case of China-Africa Related Topics

DOI

10.2991/esac-15.2015.25How to use a DOI?

Keywords

Search engines, Clustering, Online search, Webpage classification, Feature selection

Abstract

Having observed the existing search engines for online information, considering the huge (and unnecessary) amount of search results for each online search, the goal of this research work is to build on an accurate webpage classification technique, by combining feature selection techniques, and pushing the clustering concept to a next step. In this paper, we conducted experiments with various numbers of websites selected by different feature selection algorithms on a well-defined initial set of features and show that by combining some textual classification methods, we do obtain considerable classification accuracy.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Francois Tchiegue
AU  - Rui Li
AU  - Shilong Ma
PY  - 2015/08
DA  - 2015/08
TI  - The Classification Techniques of Websites for The Case of China-Africa Related Topics
BT  - Proceedings of the 2015 International Conference on Electronic Science and Automation Control
PB  - Atlantis Press
SP  - 100
EP  - 103
SN  - 2352-538X
UR  - https://doi.org/10.2991/esac-15.2015.25
DO  - 10.2991/esac-15.2015.25
ID  - Tchiegue2015/08
ER  -