Automatic generation of semantic fields for annotating web images

The overwhelming amounts of multimedia contents have triggered the need for automatically detecting the semantic concepts within the media contents. With the development of photo sharing websites such as Flickr, we are able to obtain millions of images with usersupplied tags. However, user tags tend...

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Main Authors: WANG, Gang, CHUA, Tat Seng, NGO, Chong-wah, WANG, Yong Cheng
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Language:English
Published: Institutional Knowledge at Singapore Management University 2010
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Online Access:https://ink.library.smu.edu.sg/sis_research/6622
https://ink.library.smu.edu.sg/context/sis_research/article/7625/viewcontent/C10_2149.pdf
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spelling sg-smu-ink.sis_research-76252022-01-14T03:44:38Z Automatic generation of semantic fields for annotating web images WANG, Gang CHUA, Tat Seng NGO, Chong-wah WANG, Yong Cheng The overwhelming amounts of multimedia contents have triggered the need for automatically detecting the semantic concepts within the media contents. With the development of photo sharing websites such as Flickr, we are able to obtain millions of images with usersupplied tags. However, user tags tend to be noisy, ambiguous and incomplete. In order to improve the quality of tags to annotate web images, we propose an approach to build Semantic Fields for annotating the web images. The main idea is that the images are more likely to be relevant to a given concept, if several tags to the image belong to the same Semantic Field as the target concept. Semantic Fields are determined by a set of highly semantically associated terms with high tag co-occurrences in the image corpus and in different corpora and lexica such as WordNet and Wikipedia. We conduct experiments on the NUSWIDE web image corpus and demonstrate superior performance on image annotation as compared to the state-ofthe-art approaches. 2010-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6622 info:doi/10.5555/1944566.1944715 https://ink.library.smu.edu.sg/context/sis_research/article/7625/viewcontent/C10_2149.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Databases and Information Systems
Graphics and Human Computer Interfaces
spellingShingle Databases and Information Systems
Graphics and Human Computer Interfaces
WANG, Gang
CHUA, Tat Seng
NGO, Chong-wah
WANG, Yong Cheng
Automatic generation of semantic fields for annotating web images
description The overwhelming amounts of multimedia contents have triggered the need for automatically detecting the semantic concepts within the media contents. With the development of photo sharing websites such as Flickr, we are able to obtain millions of images with usersupplied tags. However, user tags tend to be noisy, ambiguous and incomplete. In order to improve the quality of tags to annotate web images, we propose an approach to build Semantic Fields for annotating the web images. The main idea is that the images are more likely to be relevant to a given concept, if several tags to the image belong to the same Semantic Field as the target concept. Semantic Fields are determined by a set of highly semantically associated terms with high tag co-occurrences in the image corpus and in different corpora and lexica such as WordNet and Wikipedia. We conduct experiments on the NUSWIDE web image corpus and demonstrate superior performance on image annotation as compared to the state-ofthe-art approaches.
format text
author WANG, Gang
CHUA, Tat Seng
NGO, Chong-wah
WANG, Yong Cheng
author_facet WANG, Gang
CHUA, Tat Seng
NGO, Chong-wah
WANG, Yong Cheng
author_sort WANG, Gang
title Automatic generation of semantic fields for annotating web images
title_short Automatic generation of semantic fields for annotating web images
title_full Automatic generation of semantic fields for annotating web images
title_fullStr Automatic generation of semantic fields for annotating web images
title_full_unstemmed Automatic generation of semantic fields for annotating web images
title_sort automatic generation of semantic fields for annotating web images
publisher Institutional Knowledge at Singapore Management University
publishDate 2010
url https://ink.library.smu.edu.sg/sis_research/6622
https://ink.library.smu.edu.sg/context/sis_research/article/7625/viewcontent/C10_2149.pdf
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