Studies on mobile agents for query retrieval and web page categorization using neural networks

Mobile agent is an emerging technology that is gaining momentum in the eld of distributed computing. There are some advantages in using the mobile agent technology compared with a traditional client-server solution. For example, it can reduce a network traffic, it can support a large scale of comput...

Full description

Saved in:

Bibliographic Details
Main Author:	Selamat, Ali
Format:	Thesis
Language:	English
Published:	2003
Subjects:	ZA4050 Electronic information resources
Online Access:	http://eprints.utm.my/id/eprint/3091/1/AliSelamatThesis2003.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.3091
record_format	uketd_dc
spelling	my-utm-ep.30912018-06-25T00:46:11Z Studies on mobile agents for query retrieval and web page categorization using neural networks 2003 Selamat, Ali ZA4050 Electronic information resources Mobile agent is an emerging technology that is gaining momentum in the eld of distributed computing. There are some advantages in using the mobile agent technology compared with a traditional client-server solution. For example, it can reduce a network traffic, it can support a large scale of computations with many computers in a distributed environment, it allows the use of disconnected computing for processing user queries, and it provides more exibility in the development and maintenance of distributed applications. The goal of this research is based on the application of mobile agent technology in supporting the query retrieval process from the World Wide Web (WWW). Specically, the methods of dispatching the mobile agents to retrieve the query results from the search engines in WWW have been investigated. We have also considered the ranking and classifcation methods applied to the query results that have been retrieved by the mobile agents. The scopes of the research are as follows: First, the effectiveness of mobile agent for query retrieval using the off-line and on-line approaches is investigated. We have found that the query retrieval using the off-line approach by the mobile agent is better compared with the on-line approach. Second, the ranking of query retrieval results that have been retrieved by the mobile agents using the Number of Ordering Score (NROS) is investigated. The Precision of the query results using the NROS is higher than the Recall scores. It indicates that from all of the documents returned from the query, a large proportion of the documents is relevant to the user by using the NROS approach. Third, the performance of mobile agents for query retrieval using an extended hierarchical query retrieval (EHQR) approach compared with the hierarchical query retrieval (HQR) approach is investigated. The result shows that the total routing time taken by the mobile agents to retrieve the query results using the EHQR approach is less compared with the HQR approach. Fourth, the classification of news web pages retrieved by the mobile agents using neural networks based on a background knowledge is evaluated. A new web news categorization approach, namely, a Web Page Classication Method (WPCM) is proposed. The WPCM uses a neural network with inputs obtained by both the principal components and class prole-based features (CPBF). The experimental evaluation demonstrates that the WPCM provides acceptable classification accuracy with the sports news datasets. Finally, we have also overcome the limitation of the principal component analysis-neural networks (PCA-NN method) in supervised data where the characteristic variables that describe smaller classes tend to be lost as a result of the dimensionality reduction by using the WPCM. The classification accuracy on the small classes can be improved although they have been reduced into a small number of principal components. 2003 Thesis http://eprints.utm.my/id/eprint/3091/ http://eprints.utm.my/id/eprint/3091/1/AliSelamatThesis2003.pdf application/pdf en public phd doctoral University of Osaka Prefecture, Graduate School of Engineering Graduate School of Engineering MONBUSHO Universiti Teknologi Malaysia (UTM)
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	ZA4050 Electronic information resources
spellingShingle	ZA4050 Electronic information resources Selamat, Ali Studies on mobile agents for query retrieval and web page categorization using neural networks
description	Mobile agent is an emerging technology that is gaining momentum in the eld of distributed computing. There are some advantages in using the mobile agent technology compared with a traditional client-server solution. For example, it can reduce a network traffic, it can support a large scale of computations with many computers in a distributed environment, it allows the use of disconnected computing for processing user queries, and it provides more exibility in the development and maintenance of distributed applications. The goal of this research is based on the application of mobile agent technology in supporting the query retrieval process from the World Wide Web (WWW). Specically, the methods of dispatching the mobile agents to retrieve the query results from the search engines in WWW have been investigated. We have also considered the ranking and classifcation methods applied to the query results that have been retrieved by the mobile agents. The scopes of the research are as follows: First, the effectiveness of mobile agent for query retrieval using the off-line and on-line approaches is investigated. We have found that the query retrieval using the off-line approach by the mobile agent is better compared with the on-line approach. Second, the ranking of query retrieval results that have been retrieved by the mobile agents using the Number of Ordering Score (NROS) is investigated. The Precision of the query results using the NROS is higher than the Recall scores. It indicates that from all of the documents returned from the query, a large proportion of the documents is relevant to the user by using the NROS approach. Third, the performance of mobile agents for query retrieval using an extended hierarchical query retrieval (EHQR) approach compared with the hierarchical query retrieval (HQR) approach is investigated. The result shows that the total routing time taken by the mobile agents to retrieve the query results using the EHQR approach is less compared with the HQR approach. Fourth, the classification of news web pages retrieved by the mobile agents using neural networks based on a background knowledge is evaluated. A new web news categorization approach, namely, a Web Page Classication Method (WPCM) is proposed. The WPCM uses a neural network with inputs obtained by both the principal components and class prole-based features (CPBF). The experimental evaluation demonstrates that the WPCM provides acceptable classification accuracy with the sports news datasets. Finally, we have also overcome the limitation of the principal component analysis-neural networks (PCA-NN method) in supervised data where the characteristic variables that describe smaller classes tend to be lost as a result of the dimensionality reduction by using the WPCM. The classification accuracy on the small classes can be improved although they have been reduced into a small number of principal components.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Selamat, Ali
author_facet	Selamat, Ali
author_sort	Selamat, Ali
title	Studies on mobile agents for query retrieval and web page categorization using neural networks
title_short	Studies on mobile agents for query retrieval and web page categorization using neural networks
title_full	Studies on mobile agents for query retrieval and web page categorization using neural networks
title_fullStr	Studies on mobile agents for query retrieval and web page categorization using neural networks
title_full_unstemmed	Studies on mobile agents for query retrieval and web page categorization using neural networks
title_sort	studies on mobile agents for query retrieval and web page categorization using neural networks
granting_institution	University of Osaka Prefecture, Graduate School of Engineering
granting_department	Graduate School of Engineering
publishDate	2003
url	http://eprints.utm.my/id/eprint/3091/1/AliSelamatThesis2003.pdf
_version_	1747814438745931776

Studies on mobile agents for query retrieval and web page categorization using neural networks

Similar Items