Improve feature selection method of web page language identification using fuzzy ARTMAP

被引：2
|
作者：
Ng C.-C. [1 ]
Selamat A. [1 ]
机构：
[1] Faculty of Computer Science and Information Systems, University of Technology Malaysia (UTM), Johor Bahru, Johor
来源：
International Journal of Intelligent Information and Database Systems | 2010年 / 4卷 / 06期
关键词：
Feature selection; Fuzzy ARTMAP; N-grams frequency; Web page language identification;
D O I：
10.1504/IJIIDS.2010.036897
中图分类号：
学科分类号：
摘要：
The information available in languages other than English on the World Wide Web and global information systems is increasing significantly. Different languages can be produced by using one particular script such as Arabic, Persian, Urdu and Pashto that use Arabic script letters. The issue is how to produce reliable features of a web page that is to undergo language identification. Incorrectly identifying the language results in garbled translations as well as faulty and incomplete analyses. The aim of this study is to enhance the effectiveness of feature selection method of web page language identification. We have investigated total N-grams, N-grams frequency, N-grams frequency document frequency, and N-grams frequency inverse document frequency of web page language identification. From the experimental results, it is proven that N-grams frequency gives the most promising result compared to other feature selection methods. Copyright © 2010 Inderscience Enterprises Ltd.
引用
收藏
页码：629 / 642
页数：13
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