Ontology based keyword suggestion for image processing domain

The ontology-based keyword search system is a system that will identify related keywords for a search session. The internet is becoming increasingly important day by day so does the search engines that help users to retrieve information from the internet. However, the query inefficiency is still a p...

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Main Author:	Ooi, Jessie
Format:	Thesis
Language:	English
Published:	2018
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/26093/1/Ontology%20based%20keyword%20suggestion%20for%20image%20processing.pdf
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id	my-ump-ir.26093
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spelling	my-ump-ir.260932019-10-18T03:42:59Z Ontology based keyword suggestion for image processing domain 2018-09 Ooi, Jessie QA75 Electronic computers. Computer science The ontology-based keyword search system is a system that will identify related keywords for a search session. The internet is becoming increasingly important day by day so does the search engines that help users to retrieve information from the internet. However, the query inefficiency is still a problem. This is often caused by the inappropriate keywords given by the users. A junior researcher often does not have the ability to come out with suitable keywords that can describe their information needs accurately due to the lack of basic knowledge in the domain. To improve the junior researcher’s searching experience, the query modification methods have been investigated. Based on this, an ontology-based keywords search system has been proposed. The development of the ontology-based keywords search system was divided into two different part. The first part of the development is the ontology development. Image processing has been selected as the domain for the ontology. The methodology used for the development of the ontology was based on the ontology development 101. The ontology developed were based on research articles and Image Processing reference books and the tools used during the ontology development is Protege. On the other hand, the proposed system was developed using SPARQL to query the information from image processing ontology. The evaluations of the ontology and the proposed system had been carried out using 4 different methods. The first evaluation used is the reasoning. This is to ensure there is no logical contradiction in the ontology. The second evaluation is the metric-based evaluation. The evaluation has shown that the ontology has a detailed type of knowledge representation and based on the AP of the metric-based evaluation, the ontology has the ability to present the knowledge available in the schema effectively. Furthermore, the Precision and Recall were calculated. The Precision and Recall rate of the keywords provided by the OKSS achieve a 0.78 precision rate which is 0.09 higher than the precision rate of the query suggestion provided by the Google search engine. Similarly, the query provided by the Google search engine has a lower average recall rate as compared to the OKSS’s keywords recall rate. To evaluate the usefulness (in terms of productivity, effectivity and time consumption) of the proposed approach, a user experiment has been conducted. In this study, only master students from the Faculty of Computer Systems and Software Engineering were selected. The system usability score had been calculated in this experiment where the proposed system has scored 81.62. The usability score has shown that the proposed system has achieved the study objectives. 2018-09 Thesis http://umpir.ump.edu.my/id/eprint/26093/ http://umpir.ump.edu.my/id/eprint/26093/1/Ontology%20based%20keyword%20suggestion%20for%20image%20processing.pdf pdf en public https://efind.ump.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=7827 masters Universiti Malaysia Pahang Faculty of Computer Systems and Software Engineering
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Ooi, Jessie Ontology based keyword suggestion for image processing domain
description	The ontology-based keyword search system is a system that will identify related keywords for a search session. The internet is becoming increasingly important day by day so does the search engines that help users to retrieve information from the internet. However, the query inefficiency is still a problem. This is often caused by the inappropriate keywords given by the users. A junior researcher often does not have the ability to come out with suitable keywords that can describe their information needs accurately due to the lack of basic knowledge in the domain. To improve the junior researcher’s searching experience, the query modification methods have been investigated. Based on this, an ontology-based keywords search system has been proposed. The development of the ontology-based keywords search system was divided into two different part. The first part of the development is the ontology development. Image processing has been selected as the domain for the ontology. The methodology used for the development of the ontology was based on the ontology development 101. The ontology developed were based on research articles and Image Processing reference books and the tools used during the ontology development is Protege. On the other hand, the proposed system was developed using SPARQL to query the information from image processing ontology. The evaluations of the ontology and the proposed system had been carried out using 4 different methods. The first evaluation used is the reasoning. This is to ensure there is no logical contradiction in the ontology. The second evaluation is the metric-based evaluation. The evaluation has shown that the ontology has a detailed type of knowledge representation and based on the AP of the metric-based evaluation, the ontology has the ability to present the knowledge available in the schema effectively. Furthermore, the Precision and Recall were calculated. The Precision and Recall rate of the keywords provided by the OKSS achieve a 0.78 precision rate which is 0.09 higher than the precision rate of the query suggestion provided by the Google search engine. Similarly, the query provided by the Google search engine has a lower average recall rate as compared to the OKSS’s keywords recall rate. To evaluate the usefulness (in terms of productivity, effectivity and time consumption) of the proposed approach, a user experiment has been conducted. In this study, only master students from the Faculty of Computer Systems and Software Engineering were selected. The system usability score had been calculated in this experiment where the proposed system has scored 81.62. The usability score has shown that the proposed system has achieved the study objectives.
format	Thesis
qualification_level	Master's degree
author	Ooi, Jessie
author_facet	Ooi, Jessie
author_sort	Ooi, Jessie
title	Ontology based keyword suggestion for image processing domain
title_short	Ontology based keyword suggestion for image processing domain
title_full	Ontology based keyword suggestion for image processing domain
title_fullStr	Ontology based keyword suggestion for image processing domain
title_full_unstemmed	Ontology based keyword suggestion for image processing domain
title_sort	ontology based keyword suggestion for image processing domain
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Computer Systems and Software Engineering
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/26093/1/Ontology%20based%20keyword%20suggestion%20for%20image%20processing.pdf
_version_	1783732102798245888

Ontology based keyword suggestion for image processing domain

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