Context sensitive tag expansion with information inference

Cai, Hongyun, Huang, Zi, Shao, Jie and Li, Xue (2012). Context sensitive tag expansion with information inference. In: Proceedings, Part I: 17th International Conference on Database Systems for Advanced Applications, DASFAA 2012. 17th International Conference on Database Systems for Advanced Applications, DASFAA 2012, Busan, South Korea, (440-454). 15-19 April 2012. doi:10.1007/978-3-642-29038-1_32

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Author Cai, Hongyun
Huang, Zi
Shao, Jie
Li, Xue
Title of paper Context sensitive tag expansion with information inference
Conference name 17th International Conference on Database Systems for Advanced Applications, DASFAA 2012
Conference location Busan, South Korea
Conference dates 15-19 April 2012
Proceedings title Proceedings, Part I: 17th International Conference on Database Systems for Advanced Applications, DASFAA 2012   Check publisher's open access policy
Journal name Lecture Notes in Computer Science   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2012
Sub-type Fully published paper
DOI 10.1007/978-3-642-29038-1_32
ISBN 9783642290374
ISSN 0302-9743
1611-3349
Volume 7238
Start page 440
End page 454
Total pages 15
Collection year 2013
Language eng
Abstract/Summary The exponential explosion of web image data on the Internet has been witnessed over the last few years. The precise labeling of these images is crucial to effective image retrieval. However, most existing image tagging methods discover the correlations from tag co-occurrence relationship, which leads to the limited scope of extended tags. In this paper, we study how to build a new information inference model over image tag datasets for more effective and complete tag expansion. Specifically, the proposed approach uses modified Hyperspace Analogue to Language (HAL) model instead of association rules or latent dirichlet allocations to mine the correlations between image tags. It takes advantage of context sensitive information inference to overcome the limitation caused by the tag co-occurrence based methods. The strength of this approach lies in its ability to generate additional tags that are relevant to a target image but may have weak co-occurrence relationship with the existing tags in the target image. We demonstrate the effectiveness of this proposal with extensive experiments on a large Flickr image dataset.”
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Fri, 21 Sep 2012, 19:20:36 EST by Ms Ramona Hooyer on behalf of School of Information Technol and Elec Engineering