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

TitleRetrieving and ranking unannotated images through collaboratively mining online search results
Authors
KeywordsMultimedia information retrieval
Web information retrieval
Online reference image collection
Query processing
Retrieving unannotated images
Web search mining
Issue Date2011
PublisherAssociation 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?
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.
Persistent Identifierhttp://hdl.handle.net/10722/152020
ISBN
References

 

Author Affiliations
  1. The University of Hong Kong
  2. Oak Ridge National Laboratory
DC FieldValueLanguage
dc.contributor.authorXu, Sen_US
dc.contributor.authorJiang, Hen_US
dc.contributor.authorLau, FCMen_US
dc.date.accessioned2012-06-26T06:32:34Z-
dc.date.available2012-06-26T06:32:34Z-
dc.date.issued2011en_US
dc.identifier.citationThe 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. 485-494en_US
dc.identifier.isbn978-1-4503-0717-8-
dc.identifier.urihttp://hdl.handle.net/10722/152020-
dc.description.abstractWe 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.en_US
dc.languageengen_US
dc.publisherAssociation for Computing Machinery.-
dc.relation.ispartofProceedings of the 20th ACM international conference on Information and knowledge management, CIKM 2011en_US
dc.rightsProceedings of the 20th ACM international conference on Information and knowledge management, CIKM 2011. Copyright © Association for Computing Machinery.-
dc.subjectMultimedia information retrievalen_US
dc.subjectWeb information retrievalen_US
dc.subjectOnline reference image collectionen_US
dc.subjectQuery processingen_US
dc.subjectRetrieving unannotated imagesen_US
dc.subjectWeb search miningen_US
dc.titleRetrieving and ranking unannotated images through collaboratively mining online search resultsen_US
dc.typeConference_Paperen_US
dc.identifier.emailJiang, H: jianghao@hku.hken_US
dc.identifier.emailLau, FCM: fcmlau@cs.hku.hk-
dc.identifier.authorityLau, FCM=rp00221en_US
dc.description.naturelink_to_OA_fulltexten_US
dc.identifier.doi10.1145/2063576.2063650en_US
dc.identifier.scopuseid_2-s2.0-83055191902en_US
dc.identifier.hkuros211544-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-83055191902&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage485en_US
dc.identifier.epage494en_US
dc.publisher.placeUnited States-
dc.description.otherThe 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.scopusauthoridLau, FCM=7102749723en_US
dc.identifier.scopusauthoridJiang, H=55017654000en_US
dc.identifier.scopusauthoridXu, S=7404439278en_US

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