Conference Paper: Retrieving and ranking unannotated images through collaboratively mining online search results

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Title	Retrieving and ranking unannotated images through collaboratively mining online search results
Authors	Xu, S2 Jiang, H1 Lau, FCM1
Keywords	Multimedia information retrieval Web information retrieval Online reference image collection Query processing Retrieving unannotated images Web search mining
Issue Date	2011
Publisher	Association for Computing Machinery.
Citation	The 20th ACM international conference on Information and knowledge management (CIKM 2011), Glasgow, Scotland, UK., 24-28 October 2011. In Proceedings of the 20th ACM CIKM, 2011, p. 485-494 [How to Cite?] DOI: http://dx.doi.org/10.1145/2063576.2063650
Abstract	We present a new image search and ranking algorithm for retrieving unannotated images by collaboratively mining online search results which consist of online image and text search results. The online image search results are leveraged as reference examples to perform content-based image search over unannotated images. The online text search results are utilized to estimate the reference images' relevance to the search query. The key feature of our method is its capability to deal with unreliable online image search results through jointly mining visual and textual aspects of online search results. Through such collaborative mining, our algorithm infers the relevance of an online search result image to a text query. Once we obtain the estimate of query relevance score for each online image search result, we can selectively use query specific online search result images as reference examples for retrieving and ranking unannotated images. We tested our algorithm both on the standard public image datasets and several modestly sized personal photo collections. We also compared our method with two well-known peer methods. The results indicate that our algorithm is superior to existing content-based image search algorithms for retrieving and ranking unannotated images. © 2011 ACM.
ISBN	978-1-4503-0717-8
DOI	http://dx.doi.org/10.1145/2063576.2063650
References	References in Scopus

DC Field	Value
dc.contributor.author	Xu, S
dc.contributor.author	Jiang, H
dc.contributor.author	Lau, FCM
dc.date.accessioned	2012-06-26T06:32:34Z
dc.date.available	2012-06-26T06:32:34Z
dc.date.issued	2011
dc.description.abstract	We present a new image search and ranking algorithm for retrieving unannotated images by collaboratively mining online search results which consist of online image and text search results. The online image search results are leveraged as reference examples to perform content-based image search over unannotated images. The online text search results are utilized to estimate the reference images' relevance to the search query. The key feature of our method is its capability to deal with unreliable online image search results through jointly mining visual and textual aspects of online search results. Through such collaborative mining, our algorithm infers the relevance of an online search result image to a text query. Once we obtain the estimate of query relevance score for each online image search result, we can selectively use query specific online search result images as reference examples for retrieving and ranking unannotated images. We tested our algorithm both on the standard public image datasets and several modestly sized personal photo collections. We also compared our method with two well-known peer methods. The results indicate that our algorithm is superior to existing content-based image search algorithms for retrieving and ranking unannotated images. © 2011 ACM.
dc.description.nature	link_to_OA_fulltext
dc.description.other	The 20th ACM international conference on Information and knowledge management (CIKM 2011), Glasgow, Scotland, UK., 24-28 October 2011. In Proceedings of the 20th ACM CIKM, 2011, p. 485-494
dc.identifier.citation	The 20th ACM international conference on Information and knowledge management (CIKM 2011), Glasgow, Scotland, UK., 24-28 October 2011. In Proceedings of the 20th ACM CIKM, 2011, p. 485-494 [How to Cite?] DOI: http://dx.doi.org/10.1145/2063576.2063650
dc.identifier.doi	http://dx.doi.org/10.1145/2063576.2063650
dc.identifier.epage	494
dc.identifier.hkuros	211544
dc.identifier.isbn	978-1-4503-0717-8
dc.identifier.scopus	eid_2-s2.0-83055191902
dc.identifier.spage	485
dc.identifier.uri	http://hdl.handle.net/10722/152020
dc.language	eng
dc.publisher	Association for Computing Machinery.
dc.publisher.place	United States
dc.relation.ispartof	Proceedings of the 20th ACM international conference on Information and knowledge management, CIKM 2011
dc.relation.references	References in Scopus
dc.rights	Proceedings of the 20th ACM international conference on Information and knowledge management, CIKM 2011. Copyright © Association for Computing Machinery.
dc.subject	Multimedia information retrieval
dc.subject	Web information retrieval
dc.subject	Online reference image collection
dc.subject	Query processing
dc.subject	Retrieving unannotated images
dc.subject	Web search mining
dc.title	Retrieving and ranking unannotated images through collaboratively mining online search results
dc.type	Conference_Paper

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Author Affiliations

The University of Hong Kong
Oak Ridge National Laboratory