CFM@MediaEval 2017 Retrieving diverse social images task via re-ranking and hierarchical clustering

Peng, L; Bin, Y; Fu, X; Zhou, J; Yang, Y; Shen, HT

CFM@MediaEval 2017 Retrieving diverse social images task via re-ranking and hierarchical clustering

Peng, L Bin, Y Fu, X Zhou, J Yang, Y Shen, HT

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Publication Type:: Conference Proceeding
Citation:: CEUR Workshop Proceedings, 2017, 1984
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Peng, L	en_US
dc.contributor.author	Bin, Y	en_US
dc.contributor.author	Fu, X	en_US
dc.contributor.author	Zhou, J	en_US
dc.contributor.author	Yang, Y	en_US
dc.contributor.author	Shen, HT	en_US
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	CEUR Workshop Proceedings, 2017, 1984	en_US
dc.identifier.issn	1613-0073	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126720
dc.description.abstract	© 2017 Author/owner(s). This paper presents an approach based on re-ranking and hierarchical clustering (HC) for MediaEval 2017 Retrieving Diverse Social Images Task. The experimental results on the development and test set demonstrate that the proposed approach can significantly improve relevance and visual diversity of the query results. Our approach achieves a good tradeoff between relevance and diversity and a result in F1@20 of 0.6533 for the employed test data.	en_US
dc.relation.ispartof	CEUR Workshop Proceedings	en_US
dc.title	CFM@MediaEval 2017 Retrieving diverse social images task via re-ranking and hierarchical clustering	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1984	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	1984	en_US

Abstract:

© 2017 Author/owner(s). This paper presents an approach based on re-ranking and hierarchical clustering (HC) for MediaEval 2017 Retrieving Diverse Social Images Task. The experimental results on the development and test set demonstrate that the proposed approach can significantly improve relevance and visual diversity of the query results. Our approach achieves a good tradeoff between relevance and diversity and a result in F1@20 of 0.6533 for the employed test data.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/126720