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A webpage classification system usin...

Sun, Bo.

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A webpage classification system using genetic algorithm.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A webpage classification system using genetic algorithm./
Author:	Sun, Bo.
Description:	85 p.
Notes:	Source: Masters Abstracts International, Volume: 43-01, page: 0246.
Contained By:	Masters Abstracts International43-01.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1421932
ISBN:	0496266756

A webpage classification system using genetic algorithm.
Sun, Bo.

A webpage classification system using genetic algorithm. - 85 p.

Source: Masters Abstracts International, Volume: 43-01, page: 0246.

Thesis (M.S.)--Lamar University - Beaumont, 2004.

Because of an exponential increase of data available on the web, an efficient and accurate method for classifying this huge amount of data is very essential for fast information retrieval. This thesis presents a genetic algorithm approach for hierarchical web page categorization. Each category is represented by a keyword set with associated weights. Weights are evolved by the genetic algorithms, which performs a good solution for optimizing the properties of categories. Similarity formula is applied to calculate the similarity between the test webpage and the test category. Our experimental target is Yahoo.com. All 34,314 web pages under 11 different level categories are collected for training and testing. The experimental results show that our approach is very promising. Our approach relies on the existence of good quality texts for training. More work should be undertaken in the future to find the higher quality training web pages, which should lead to a better classification results.

ISBN: 0496266756Subjects--Topical Terms:

626642
Computer Science.

A webpage classification system using genetic algorithm.
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020 $a 0496266756
035 $a (UnM)AAI1421932
035 $a AAI1421932
040 $a UnM $c UnM
100 1 $a Sun, Bo. $3 1913958
245 1 2 $a A webpage classification system using genetic algorithm.
300 $a 85 p.
500 $a Source: Masters Abstracts International, Volume: 43-01, page: 0246.
500 $a Adviser: Dehu Qi.
502 $a Thesis (M.S.)--Lamar University - Beaumont, 2004.
520 $a Because of an exponential increase of data available on the web, an efficient and accurate method for classifying this huge amount of data is very essential for fast information retrieval. This thesis presents a genetic algorithm approach for hierarchical web page categorization. Each category is represented by a keyword set with associated weights. Weights are evolved by the genetic algorithms, which performs a good solution for optimizing the properties of categories. Similarity formula is applied to calculate the similarity between the test webpage and the test category. Our experimental target is Yahoo.com. All 34,314 web pages under 11 different level categories are collected for training and testing. The experimental results show that our approach is very promising. Our approach relies on the existence of good quality texts for training. More work should be undertaken in the future to find the higher quality training web pages, which should lead to a better classification results.
590 $a School code: 0424.
650 4 $a Computer Science. $3 626642
650 4 $a Information Science. $3 1017528
690 $a 0984
690 $a 0723
710 2 0 $a Lamar University - Beaumont. $3 1020444
773 0 $t Masters Abstracts International $g 43-01.
790 1 0 $a Qi, Dehu, $e advisor
790 $a 0424
791 $a M.S.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1421932