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Ontology-based indexing of annotated images using semantic DNA and vector space model

The study presented in this paper focuses on the preprocessing stage of image retrieval by proposing an ontology based indexing approach which captures the meaning of image annotations by extracting the semantic importance of the words in them. The indexing algorithm is based on the classic vector...

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Main Authors: Engku Fadzli Hasan, Syed Abdullah, Setchi, Rossitza
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
T Technology (General)
ZA Information resources
Online Access:http://eprints.unisza.edu.my/350/1/FH03-FIK-15-02477.pdf
http://eprints.unisza.edu.my/350/
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spelling my-unisza-ir.3502020-10-21T06:11:13Z http://eprints.unisza.edu.my/350/ Ontology-based indexing of annotated images using semantic DNA and vector space model Engku Fadzli Hasan, Syed Abdullah Setchi, Rossitza T Technology (General) ZA Information resources The study presented in this paper focuses on the preprocessing stage of image retrieval by proposing an ontology based indexing approach which captures the meaning of image annotations by extracting the semantic importance of the words in them. The indexing algorithm is based on the classic vector space model that is adapted by employing index weighting and a word sense disambiguation. It uses sets of Semantic DNA, extracted from a lexical ontology, to represent the images in a vector space. As discussed in the paper, the use of Semantic DNA in text-based image retrieval aims to overcome some of the major drawbacks of well known traditional approaches such as ‘bags of words’ and term frequency- (TF) based indexing. The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. The experimental results show that the proposed ontology-based approach generates a better-quality index which captures the conceptual meaning of the image annotations. 2014 Conference or Workshop Item NonPeerReviewed text en http://eprints.unisza.edu.my/350/1/FH03-FIK-15-02477.pdf Engku Fadzli Hasan, Syed Abdullah and Setchi, Rossitza (2014) Ontology-based indexing of annotated images using semantic DNA and vector space model. In: 2011 International Conference on Semantic Technology and Information Retrieval (STAIR 2011), 28-29 June 2011, Putrajaya.
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic T Technology (General)
ZA Information resources
spellingShingle T Technology (General)
ZA Information resources
Engku Fadzli Hasan, Syed Abdullah
Setchi, Rossitza
Ontology-based indexing of annotated images using semantic DNA and vector space model
description The study presented in this paper focuses on the preprocessing stage of image retrieval by proposing an ontology based indexing approach which captures the meaning of image annotations by extracting the semantic importance of the words in them. The indexing algorithm is based on the classic vector space model that is adapted by employing index weighting and a word sense disambiguation. It uses sets of Semantic DNA, extracted from a lexical ontology, to represent the images in a vector space. As discussed in the paper, the use of Semantic DNA in text-based image retrieval aims to overcome some of the major drawbacks of well known traditional approaches such as ‘bags of words’ and term frequency- (TF) based indexing. The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. The experimental results show that the proposed ontology-based approach generates a better-quality index which captures the conceptual meaning of the image annotations.
format Conference or Workshop Item
author Engku Fadzli Hasan, Syed Abdullah
Setchi, Rossitza
author_facet Engku Fadzli Hasan, Syed Abdullah
Setchi, Rossitza
author_sort Engku Fadzli Hasan, Syed Abdullah
title Ontology-based indexing of annotated images using semantic DNA and vector space model
title_short Ontology-based indexing of annotated images using semantic DNA and vector space model
title_full Ontology-based indexing of annotated images using semantic DNA and vector space model
title_fullStr Ontology-based indexing of annotated images using semantic DNA and vector space model
title_full_unstemmed Ontology-based indexing of annotated images using semantic DNA and vector space model
title_sort ontology-based indexing of annotated images using semantic dna and vector space model
publishDate 2014
url http://eprints.unisza.edu.my/350/1/FH03-FIK-15-02477.pdf
http://eprints.unisza.edu.my/350/
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score 13.211869

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