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10.1145/2872518.2889413acmotherconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
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Multimodal Content-Aware Image Thumbnailing

Published: 11 April 2016 Publication History

Abstract

News article recommendation has the key problem of needing to eliminate the redundant information in a ranked list in order to provide more relevant information within a limited time and space. In this study, we tackle this problem by using image thumbnailing, which can be regarded as the summarization of news images. We propose a multimodal image thumbnailing method considering news text as well as images themselves. We evaluate this approach on a real data set based on news articles that appeared on Yahoo! JAPAN. Experimental results demonstrate the effectiveness of our proposed method.

References

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R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In ¥em CVPR, 2014.
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L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on PAMI, 1998.
[3]
A. Karpathy and L. Fei-Fei. Deep visual-semantic alignments for generating image descriptions. In CVPR, 2015.
[4]
K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556, 2014.
[5]
B. Suh, H. Ling, B. B. Bederson, and J. D. W. Automatic thumbnail cropping and its effectiveness. In UIST, 2015.

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Published In

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WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide Web
April 2016
1094 pages
ISBN:9781450341448
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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  • IW3C2: International World Wide Web Conference Committee

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 11 April 2016

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Author Tags

  1. convolutional neural networks
  2. image thumbnaililing
  3. multimodal learning

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  • Poster

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WWW '16
Sponsor:
  • IW3C2
WWW '16: 25th International World Wide Web Conference
April 11 - 15, 2016
Québec, Montréal, Canada

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WWW '16 Companion Paper Acceptance Rate 115 of 727 submissions, 16%;
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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