Semi-supervised Multi-view Individual and Sharable Feature Learning for Webpage Classification-Reference-Cited by-同舟云学术

Semi-supervised Multi-view Individual and Sharable Feature Learning for Webpage Classification

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:The World Wide Web Conference on - WWW '19
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Author:

Wu Fei¹,Jing Xiao-Yuan²,Zhou Jun¹,Ji Yimu³,Lan Chao⁴,Huang Qinghua⁵,Wang Ruchuan³

Affiliation:

1. College of Automation, Nanjing University of Posts and Telecommunications China

2. School of Computer, Wuhan University, College of Automation, Nanjing University of Posts and Telecommunications China

3. College of Computer, Nanjing University of Posts and Telecommunications China

4. Department of Computer Science, University of Wyoming United States

5. School of Science, Nanjing University of Posts and Telecommunications China

Publisher

ACM Press

Reference40 articles.

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2. Chen Gong, Dacheng Tao, Stephen J Maybank, Wei Liu, Guoliang Kang, and Jie Yang. 2016. Multi-modal curriculum learning for semi-supervised image classification. IEEE Transactions on Image Processing 25, 7 (2016), 3249-3260.

3. Junlin Hu, Jiwen Lu, and Yap-Peng Tan. 2018. Sharable and individual multi-view metric learning. IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 9(2018), 2281-2288.

4. Yu Jiang, Jing Liu, Zechao Li, and Hanqing Lu. 2014. Semi-supervised unified latent factor learning with multi-view data. Machine Vision and Applications 25, 7 (2014), 1635-1645.

5. Xiao-Yuan Jing, Qian Liu, Fei Wu, Baowen Xu, Yang-Ping Zhu, and Songcan Chen. 2015. Web page classification based on uncorrelated semi-supervised intra-view and inter-view manifold discriminant feature extraction. In Proceedings of the 24th International Joint Conferences on Artificial Intelligence. 2255-2261.

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