Social tag relevance estimation via ranking-oriented neighbour voting

User-generated tags associated with social images are frequently imprecise and incomplete. Therefore, a fundamental challenge in tag-based applications is the problem of tag relevance estimation, which concerns how to interpret and quantify the relevance of a tag with respect to the contents of an i...

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Main Authors: CUI, Chaoran, SHEN, Jialie, MA, Jun, LIAN, Tao
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/3541
https://ink.library.smu.edu.sg/context/sis_research/article/4542/viewcontent/SocialTagRelevanceLeranviaRankNeighborVoting_2015_MM.pdf
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spelling sg-smu-ink.sis_research-45422017-03-27T03:46:46Z Social tag relevance estimation via ranking-oriented neighbour voting CUI, Chaoran SHEN, Jialie MA, Jun LIAN, Tao User-generated tags associated with social images are frequently imprecise and incomplete. Therefore, a fundamental challenge in tag-based applications is the problem of tag relevance estimation, which concerns how to interpret and quantify the relevance of a tag with respect to the contents of an image. In this paper, we address the key problem from a new perspective of learning to rank, and develop a novel approach to facilitate tag relevance estimation to directly optimize the ranking performance of tag-based image search. A supervision step is introduced into the neighbour voting scheme, in which tag relevance is estimated by accumulating votes from visual neighbours. Through explicitly modelling the neighbour weights and tag correlations, the risk of making heuristic assumptions is effectively avoided for conventional methods. Extensive experiments on a benchmark dataset in comparison with the state-of-the-art methods demonstrate the promise of our approach. 2015-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3541 info:doi/10.1145/2733373.2806358 https://ink.library.smu.edu.sg/context/sis_research/article/4542/viewcontent/SocialTagRelevanceLeranviaRankNeighborVoting_2015_MM.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 Learning to rank Neighbour voting Tag relevance estimation Tag-based image search Computer Sciences Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Learning to rank
Neighbour voting
Tag relevance estimation
Tag-based image search
Computer Sciences
Databases and Information Systems
spellingShingle Learning to rank
Neighbour voting
Tag relevance estimation
Tag-based image search
Computer Sciences
Databases and Information Systems
CUI, Chaoran
SHEN, Jialie
MA, Jun
LIAN, Tao
Social tag relevance estimation via ranking-oriented neighbour voting
description User-generated tags associated with social images are frequently imprecise and incomplete. Therefore, a fundamental challenge in tag-based applications is the problem of tag relevance estimation, which concerns how to interpret and quantify the relevance of a tag with respect to the contents of an image. In this paper, we address the key problem from a new perspective of learning to rank, and develop a novel approach to facilitate tag relevance estimation to directly optimize the ranking performance of tag-based image search. A supervision step is introduced into the neighbour voting scheme, in which tag relevance is estimated by accumulating votes from visual neighbours. Through explicitly modelling the neighbour weights and tag correlations, the risk of making heuristic assumptions is effectively avoided for conventional methods. Extensive experiments on a benchmark dataset in comparison with the state-of-the-art methods demonstrate the promise of our approach.
format text
author CUI, Chaoran
SHEN, Jialie
MA, Jun
LIAN, Tao
author_facet CUI, Chaoran
SHEN, Jialie
MA, Jun
LIAN, Tao
author_sort CUI, Chaoran
title Social tag relevance estimation via ranking-oriented neighbour voting
title_short Social tag relevance estimation via ranking-oriented neighbour voting
title_full Social tag relevance estimation via ranking-oriented neighbour voting
title_fullStr Social tag relevance estimation via ranking-oriented neighbour voting
title_full_unstemmed Social tag relevance estimation via ranking-oriented neighbour voting
title_sort social tag relevance estimation via ranking-oriented neighbour voting
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/3541
https://ink.library.smu.edu.sg/context/sis_research/article/4542/viewcontent/SocialTagRelevanceLeranviaRankNeighborVoting_2015_MM.pdf
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