Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects

Digital resource objects (DRO) refer to information that are structured which elaborate, describe, and ease retrieval, usage and management of information resources. Lately, the need for accessing the content of DROs has been addressed differently by data retrieval (DR) and information retrieval...

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Main Author:	Alma’aitah, Wafa’ Za’al Mohammad
Format:	Thesis
Language:	English
Published:	2020
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/54014/1/WAFA%E2%80%99%20ZA%E2%80%99AL%20MOHAMMAD%20ALMA%E2%80%99AITAH.pdf
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spelling	my-usm-ep.540142022-08-12T01:51:22Z Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects 2020-03 Alma’aitah, Wafa’ Za’al Mohammad QA75.5-76.95 Electronic computers. Computer science Digital resource objects (DRO) refer to information that are structured which elaborate, describe, and ease retrieval, usage and management of information resources. Lately, the need for accessing the content of DROs has been addressed differently by data retrieval (DR) and information retrieval (IR) research communities. DR is found to be inadequate in providing enriched metadata content and may fail to enhance the retrieval performance. In this thesis, an IR framework is proposed which consists of three main stages: enhanced document expansion (EDE) method, adaptive structured Dirichlet smoothing (ASDS) model, and semantic query expansion (SQE) method. The first stage involves proposing an EDE method in which a new procedure is introduced to increase each metadata unit content according to some specific steps by adding new information which is more relevant and closer to each metadata unit in each document while the second stage involves proposing an ASDS model that has two scenarios to improve the Dirichlet smoothing model. The first scenario is to enhance the model by taking into account of the document structure as in the proposed structured Dirichlet smoothing (SDS) model while the second scenario is to modify the parameters used in the model as in the proposed Adaptive Dirichlet smoothing (ADS) model. The third stage of the proposed framework involves the proposed SQE method to enhance the retrieval performance of DROs by improving the quality of candidate terms that are added semantically to the entire query term. 2020-03 Thesis http://eprints.usm.my/54014/ http://eprints.usm.my/54014/1/WAFA%E2%80%99%20ZA%E2%80%99AL%20MOHAMMAD%20ALMA%E2%80%99AITAH.pdf application/pdf en public phd doctoral Perpustakaan Hamzah Sendut Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Alma’aitah, Wafa’ Za’al Mohammad Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects
description	Digital resource objects (DRO) refer to information that are structured which elaborate, describe, and ease retrieval, usage and management of information resources. Lately, the need for accessing the content of DROs has been addressed differently by data retrieval (DR) and information retrieval (IR) research communities. DR is found to be inadequate in providing enriched metadata content and may fail to enhance the retrieval performance. In this thesis, an IR framework is proposed which consists of three main stages: enhanced document expansion (EDE) method, adaptive structured Dirichlet smoothing (ASDS) model, and semantic query expansion (SQE) method. The first stage involves proposing an EDE method in which a new procedure is introduced to increase each metadata unit content according to some specific steps by adding new information which is more relevant and closer to each metadata unit in each document while the second stage involves proposing an ASDS model that has two scenarios to improve the Dirichlet smoothing model. The first scenario is to enhance the model by taking into account of the document structure as in the proposed structured Dirichlet smoothing (SDS) model while the second scenario is to modify the parameters used in the model as in the proposed Adaptive Dirichlet smoothing (ADS) model. The third stage of the proposed framework involves the proposed SQE method to enhance the retrieval performance of DROs by improving the quality of candidate terms that are added semantically to the entire query term.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Alma’aitah, Wafa’ Za’al Mohammad
author_facet	Alma’aitah, Wafa’ Za’al Mohammad
author_sort	Alma’aitah, Wafa’ Za’al Mohammad
title	Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects
title_short	Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects
title_full	Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects
title_fullStr	Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects
title_full_unstemmed	Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects
title_sort	document and query expansion method with dirichlet smoothing model for retrieval of metadata content in digital resource objects
granting_institution	Perpustakaan Hamzah Sendut
granting_department	Pusat Pengajian Sains Komputer
publishDate	2020
url	http://eprints.usm.my/54014/1/WAFA%E2%80%99%20ZA%E2%80%99AL%20MOHAMMAD%20ALMA%E2%80%99AITAH.pdf
_version_	1747822271091703808

Document And Query Expansion Method With Dirichlet Smoothing Model For Retrieval Of Metadata Content In Digital Resource Objects

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