Modelling Image Semantic Descriptions from Web 2.0 Documents using a Hybrid Approach.
Modelling Image Semantic Descriptions from Web 2.0 Documents using a Hybrid Approach.
With the increasing amount of multimedia content on the web added as user generated content in Web 2.0 websites, conventional multimedia information retrieval is presented with new challenges. It is no longer possible to rely only on meta-data based retrieval but to consider also content based techniques combined with the collective knowledge generated by users’ contributions and geo-referenced meta-data. Tagging is a modest way to annotate such documents and fails to capture a full semantic description of the document content. This report concerns ongoing research to investigate a means to identify, model and utilise semantic descriptions of the user-generated content in Web 2.0 documents using a hybrid approach. The approach consists of three main components, natural language processing, image analysis and a shared knowledge base. In this paper we describe the complete model but, as the image analysis component is in its early stages, the results focus on the natural language processing and the knowledge base. We show that the additional use of these components can improve retrieval and analysis performance over that based only on Web 2.0 tags.
Image semantic description, natural language analysis, knowledge base, ontology, semantic web.
Zakaria, Lailatul Qadri
c62d1aad-8080-4a46-add7-cdeb86b53138
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Lewis, Paul
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
14 December 2009
Zakaria, Lailatul Qadri
c62d1aad-8080-4a46-add7-cdeb86b53138
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Lewis, Paul
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
Zakaria, Lailatul Qadri, Hall, Wendy and Lewis, Paul
(2009)
Modelling Image Semantic Descriptions from Web 2.0 Documents using a Hybrid Approach.
11th International Conference on Information Integration and Web-based Applications & Services (iiWAS2009), Kuala Lumpur, Malaysia.
14 - 16 Dec 2009.
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Conference or Workshop Item
(Paper)
Abstract
With the increasing amount of multimedia content on the web added as user generated content in Web 2.0 websites, conventional multimedia information retrieval is presented with new challenges. It is no longer possible to rely only on meta-data based retrieval but to consider also content based techniques combined with the collective knowledge generated by users’ contributions and geo-referenced meta-data. Tagging is a modest way to annotate such documents and fails to capture a full semantic description of the document content. This report concerns ongoing research to investigate a means to identify, model and utilise semantic descriptions of the user-generated content in Web 2.0 documents using a hybrid approach. The approach consists of three main components, natural language processing, image analysis and a shared knowledge base. In this paper we describe the complete model but, as the image analysis component is in its early stages, the results focus on the natural language processing and the knowledge base. We show that the additional use of these components can improve retrieval and analysis performance over that based only on Web 2.0 tags.
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iiwas_122_zakaria.pdf
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Published date: 14 December 2009
Additional Information:
Event Dates: 14 Dec 2009 to 16 Dec 2009
Venue - Dates:
11th International Conference on Information Integration and Web-based Applications & Services (iiWAS2009), Kuala Lumpur, Malaysia, 2009-12-14 - 2009-12-16
Keywords:
Image semantic description, natural language analysis, knowledge base, ontology, semantic web.
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 268495
URI: http://eprints.soton.ac.uk/id/eprint/268495
PURE UUID: ad6d3047-dfdf-41d2-be1d-821ba0f64522
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Date deposited: 10 Feb 2010 18:37
Last modified: 15 Mar 2024 02:33
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Contributors
Author:
Lailatul Qadri Zakaria
Author:
Paul Lewis
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