Multiple ontology-based indexing of multimedia documents on the world wide web

Mohammed Maree, Mohammed Belkhatir, Wan Fariza Paizi@Fauzi, Aseel B. Kmail, Ahmad Ewais, Muath Sabha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In order to cope with the growing need to search multimedia documents with precision on the Web, we propose a multimedia conceptual indexing framework incorporating semantic relations between annotation words. To do this, we utilize our DOM Tree-based Webpage segmentation algorithm to automatically extract surrounding textual information of the multimedia documents in Webpages. Next, we employ knowledge represented in multiple ontologies to discover the latent semantic dimensions of the surrounding textual information. As a consequence, indexes (represented as semantic networks) are constructed where nodes of each network capture words that exist in the ontologies and edges represent the semantic relations that hold between those words. To address the semantic heterogeneity problem between the produced networks, we employ a multi-level merging algorithm that combines heterogeneous networks into a more coherent network. Additionally, we utilize concept-relatedness measures to address the issue of unrecognized entities by the ontologies. We evaluate the techniques of the proposed framework using three different multimedia dataset types. Experimental results indicate that the proposed techniques are effective and precise.

Original languageEnglish
Title of host publicationIntelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016
PublisherSpringer Science and Business Media Deutschland GmbH
Pages51-62
Number of pages12
ISBN (Print)9783319396262
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 - Puerto de la Cruz, Tenerife, Spain
Duration: 15 Jun 201617 Jun 2016

Publication series

NameSmart Innovation, Systems and Technologies
Volume57
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Other

Other8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016
CountrySpain
CityPuerto de la Cruz, Tenerife
Period15/6/1617/6/16

Fingerprint

World Wide Web
Ontology
Semantics
Heterogeneous networks
Merging
Indexing
Multimedia

Keywords

  • Multimedia indexing
  • Ontology
  • Webpage segmentation

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

Cite this

Maree, M., Belkhatir, M., Paizi@Fauzi, W. F., Kmail, A. B., Ewais, A., & Sabha, M. (2016). Multiple ontology-based indexing of multimedia documents on the world wide web. In Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 (pp. 51-62). (Smart Innovation, Systems and Technologies; Vol. 57). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-39627-9_5

Multiple ontology-based indexing of multimedia documents on the world wide web. / Maree, Mohammed; Belkhatir, Mohammed; Paizi@Fauzi, Wan Fariza; Kmail, Aseel B.; Ewais, Ahmad; Sabha, Muath.

Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Springer Science and Business Media Deutschland GmbH, 2016. p. 51-62 (Smart Innovation, Systems and Technologies; Vol. 57).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Maree, M, Belkhatir, M, Paizi@Fauzi, WF, Kmail, AB, Ewais, A & Sabha, M 2016, Multiple ontology-based indexing of multimedia documents on the world wide web. in Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Smart Innovation, Systems and Technologies, vol. 57, Springer Science and Business Media Deutschland GmbH, pp. 51-62, 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016, Puerto de la Cruz, Tenerife, Spain, 15/6/16. https://doi.org/10.1007/978-3-319-39627-9_5
Maree M, Belkhatir M, Paizi@Fauzi WF, Kmail AB, Ewais A, Sabha M. Multiple ontology-based indexing of multimedia documents on the world wide web. In Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Springer Science and Business Media Deutschland GmbH. 2016. p. 51-62. (Smart Innovation, Systems and Technologies). https://doi.org/10.1007/978-3-319-39627-9_5
Maree, Mohammed ; Belkhatir, Mohammed ; Paizi@Fauzi, Wan Fariza ; Kmail, Aseel B. ; Ewais, Ahmad ; Sabha, Muath. / Multiple ontology-based indexing of multimedia documents on the world wide web. Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Springer Science and Business Media Deutschland GmbH, 2016. pp. 51-62 (Smart Innovation, Systems and Technologies).
@inproceedings{de33b9939aaa47cabfa4287cc544eb84,
title = "Multiple ontology-based indexing of multimedia documents on the world wide web",
abstract = "In order to cope with the growing need to search multimedia documents with precision on the Web, we propose a multimedia conceptual indexing framework incorporating semantic relations between annotation words. To do this, we utilize our DOM Tree-based Webpage segmentation algorithm to automatically extract surrounding textual information of the multimedia documents in Webpages. Next, we employ knowledge represented in multiple ontologies to discover the latent semantic dimensions of the surrounding textual information. As a consequence, indexes (represented as semantic networks) are constructed where nodes of each network capture words that exist in the ontologies and edges represent the semantic relations that hold between those words. To address the semantic heterogeneity problem between the produced networks, we employ a multi-level merging algorithm that combines heterogeneous networks into a more coherent network. Additionally, we utilize concept-relatedness measures to address the issue of unrecognized entities by the ontologies. We evaluate the techniques of the proposed framework using three different multimedia dataset types. Experimental results indicate that the proposed techniques are effective and precise.",
keywords = "Multimedia indexing, Ontology, Webpage segmentation",
author = "Mohammed Maree and Mohammed Belkhatir and Paizi@Fauzi, {Wan Fariza} and Kmail, {Aseel B.} and Ahmad Ewais and Muath Sabha",
year = "2016",
month = "1",
day = "1",
doi = "10.1007/978-3-319-39627-9_5",
language = "English",
isbn = "9783319396262",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "51--62",
booktitle = "Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016",
address = "Germany",

}

TY - GEN

T1 - Multiple ontology-based indexing of multimedia documents on the world wide web

AU - Maree, Mohammed

AU - Belkhatir, Mohammed

AU - Paizi@Fauzi, Wan Fariza

AU - Kmail, Aseel B.

AU - Ewais, Ahmad

AU - Sabha, Muath

PY - 2016/1/1

Y1 - 2016/1/1

N2 - In order to cope with the growing need to search multimedia documents with precision on the Web, we propose a multimedia conceptual indexing framework incorporating semantic relations between annotation words. To do this, we utilize our DOM Tree-based Webpage segmentation algorithm to automatically extract surrounding textual information of the multimedia documents in Webpages. Next, we employ knowledge represented in multiple ontologies to discover the latent semantic dimensions of the surrounding textual information. As a consequence, indexes (represented as semantic networks) are constructed where nodes of each network capture words that exist in the ontologies and edges represent the semantic relations that hold between those words. To address the semantic heterogeneity problem between the produced networks, we employ a multi-level merging algorithm that combines heterogeneous networks into a more coherent network. Additionally, we utilize concept-relatedness measures to address the issue of unrecognized entities by the ontologies. We evaluate the techniques of the proposed framework using three different multimedia dataset types. Experimental results indicate that the proposed techniques are effective and precise.

AB - In order to cope with the growing need to search multimedia documents with precision on the Web, we propose a multimedia conceptual indexing framework incorporating semantic relations between annotation words. To do this, we utilize our DOM Tree-based Webpage segmentation algorithm to automatically extract surrounding textual information of the multimedia documents in Webpages. Next, we employ knowledge represented in multiple ontologies to discover the latent semantic dimensions of the surrounding textual information. As a consequence, indexes (represented as semantic networks) are constructed where nodes of each network capture words that exist in the ontologies and edges represent the semantic relations that hold between those words. To address the semantic heterogeneity problem between the produced networks, we employ a multi-level merging algorithm that combines heterogeneous networks into a more coherent network. Additionally, we utilize concept-relatedness measures to address the issue of unrecognized entities by the ontologies. We evaluate the techniques of the proposed framework using three different multimedia dataset types. Experimental results indicate that the proposed techniques are effective and precise.

KW - Multimedia indexing

KW - Ontology

KW - Webpage segmentation

UR - http://www.scopus.com/inward/record.url?scp=84977098335&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84977098335&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-39627-9_5

DO - 10.1007/978-3-319-39627-9_5

M3 - Conference contribution

AN - SCOPUS:84977098335

SN - 9783319396262

T3 - Smart Innovation, Systems and Technologies

SP - 51

EP - 62

BT - Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016

PB - Springer Science and Business Media Deutschland GmbH

ER -