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2018 | OriginalPaper | Chapter

Hashtag Recommendation with Attention-Based Neural Image Hashtagging Network

Authors : Gaosheng Wu, Yuhua Li, Wenjin Yan, Ruixuan Li, Xiwu Gu, Qi Yang

Published in: Neural Information Processing

Publisher: Springer International Publishing

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Abstract

With the increasing number of microblog users, the hashtag recommendation task has become an important component in social media. Most hashtag recommendation related methods get relative low precisions, because hashtags are not necessarily related to the content of tweets, which makes hashtag recommendation more challenging. In this work, we propose a new sequence-to-sequence method named attention based neural image hashtagging network (A-NIH) to model sequence relationship between social images and hashtags. To the best of our knowledge, this is the first work that applies attention mechanism to the image-only hashtag recommendation tasks. Our experimental results on the real-world social image dataset shows that our model performs better than the state-of-the-art methods.

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Literature
1.
go back to reference Berendt, B., Hanser, C.: Tags are not metadata, but “just more content” - to some people. In: Proceedings of the First International Conference on Weblogs and Social Media, ICWSM 2007, Boulder, Colorado, USA, 26–28 March 2007 (2007) Berendt, B., Hanser, C.: Tags are not metadata, but “just more content” - to some people. In: Proceedings of the First International Conference on Weblogs and Social Media, ICWSM 2007, Boulder, Colorado, USA, 26–28 March 2007 (2007)
3.
go back to reference Dey, K., Shrivastava, R., Kaushik, S., Subramaniam, L.V.: Emtagger: a word embedding based novel method for hashtag recommendation on twitter. In: 2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, 18–21 November 2017, pp. 1025–1032 (2017) Dey, K., Shrivastava, R., Kaushik, S., Subramaniam, L.V.: Emtagger: a word embedding based novel method for hashtag recommendation on twitter. In: 2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, 18–21 November 2017, pp. 1025–1032 (2017)
4.
go back to reference Efron, M.: Hashtag retrieval in a microblogging environment. In: Proceeding of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010, Geneva, Switzerland, 19–23 July 2010, pp. 787–788 (2010) Efron, M.: Hashtag retrieval in a microblogging environment. In: Proceeding of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010, Geneva, Switzerland, 19–23 July 2010, pp. 787–788 (2010)
5.
go back to reference Gong, Y., Zhang, Q., Huang, X.: Hashtag recommendation for multimodal microblog posts. Neurocomputing 272, 170–177 (2018)CrossRef Gong, Y., Zhang, Q., Huang, X.: Hashtag recommendation for multimodal microblog posts. Neurocomputing 272, 170–177 (2018)CrossRef
6.
go back to reference Gong, Y., Zhang, Q.: Hashtag recommendation using attention-based convolutional neural network. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9–15 July 2016, pp. 2782–2788 (2016) Gong, Y., Zhang, Q.: Hashtag recommendation using attention-based convolutional neural network. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9–15 July 2016, pp. 2782–2788 (2016)
7.
go back to reference Huang, H., Zhang, Q., Gong, Y., Huang, X.: Hashtag recommendation using end-to-end memory networks with hierarchical attention. In: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, 11–16 December 2016, Osaka, Japan, pp. 943–952 (2016) Huang, H., Zhang, Q., Gong, Y., Huang, X.: Hashtag recommendation using end-to-end memory networks with hierarchical attention. In: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, 11–16 December 2016, Osaka, Japan, pp. 943–952 (2016)
8.
go back to reference Jocic, M., Obradovic, D., Malbasa, V., Konjo, Z.: Image tagging with an ensemble of deep convolutional neural networks. In: 2017 International Conference on Information Society and Technology, ICIST Workshops 2017, New Orleans, LA, USA, 18–21 November 2017, pp. 13–17 (2017) Jocic, M., Obradovic, D., Malbasa, V., Konjo, Z.: Image tagging with an ensemble of deep convolutional neural networks. In: 2017 International Conference on Information Society and Technology, ICIST Workshops 2017, New Orleans, LA, USA, 18–21 November 2017, pp. 13–17 (2017)
9.
go back to reference Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. CoRR abs/1412.6980 (2014) Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. CoRR abs/1412.6980 (2014)
10.
go back to reference Li, Y., Liu, T., Jiang, J., Zhang, L.: Hashtag recommendation with topical attention-based LSTM. In: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, 11–16 December 2016, Osaka, Japan, pp. 3019–3029 (2016) Li, Y., Liu, T., Jiang, J., Zhang, L.: Hashtag recommendation with topical attention-based LSTM. In: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, 11–16 December 2016, Osaka, Japan, pp. 3019–3029 (2016)
11.
go back to reference Mnih, V., Heess, N., Graves, A., Kavukcuoglu, K.: Recurrent models of visual attention. In: Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, Montreal, Quebec, Canada, 8–13 December 2014, pp. 2204–2212 (2014) Mnih, V., Heess, N., Graves, A., Kavukcuoglu, K.: Recurrent models of visual attention. In: Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, Montreal, Quebec, Canada, 8–13 December 2014, pp. 2204–2212 (2014)
12.
go back to reference Park, M., Li, H., Kim, J.: HARRISON: A benchmark on hashtag recommendation for real-world images in social networks. CoRR abs/1605.05054 (2016) Park, M., Li, H., Kim, J.: HARRISON: A benchmark on hashtag recommendation for real-world images in social networks. CoRR abs/1605.05054 (2016)
13.
go back to reference Russakovsky, O., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211–252 (2015)MathSciNetCrossRef Russakovsky, O., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211–252 (2015)MathSciNetCrossRef
14.
go back to reference Sedhai, S., Sun, A.: Hashtag recommendation for hyperlinked tweets. In: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014, Gold Coast, QLD, Australia, 06–11 July 2014, pp. 831–834 (2014) Sedhai, S., Sun, A.: Hashtag recommendation for hyperlinked tweets. In: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014, Gold Coast, QLD, Australia, 06–11 July 2014, pp. 831–834 (2014)
15.
go back to reference Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR abs/1409.1556 (2014) Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR abs/1409.1556 (2014)
16.
go back to reference Srivastava, N., Hinton, G.E., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929–1958 (2014)MathSciNetMATH Srivastava, N., Hinton, G.E., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929–1958 (2014)MathSciNetMATH
17.
go back to reference Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, 27–30 June 2016, pp. 2818–2826 (2016) Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, 27–30 June 2016, pp. 2818–2826 (2016)
18.
go back to reference Wang, L., Guo, S., Huang, W., Qiao, Y.: Places205-vggnet models for scene recognition. CoRR abs/1508.01667 (2015) Wang, L., Guo, S., Huang, W., Qiao, Y.: Places205-vggnet models for scene recognition. CoRR abs/1508.01667 (2015)
19.
go back to reference Wang, Y.: Image tag recommendation algorithm using tensor factorization. J. Multimed. 9(3), 416–422 (2014)CrossRef Wang, Y.: Image tag recommendation algorithm using tensor factorization. J. Multimed. 9(3), 416–422 (2014)CrossRef
20.
go back to reference Xu, K., et al.: Show, attend and tell: Neural image caption generation with visual attention. In: Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6–11 July 2015, pp. 2048–2057 (2015) Xu, K., et al.: Show, attend and tell: Neural image caption generation with visual attention. In: Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6–11 July 2015, pp. 2048–2057 (2015)
21.
go back to reference Zhang, Q., Wang, J., Huang, H., Huang, X., Gong, Y.: Hashtag recommendation for multimodal microblog using co-attention network. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, 19–25 August 2017, pp. 3420–3426 (2017) Zhang, Q., Wang, J., Huang, H., Huang, X., Gong, Y.: Hashtag recommendation for multimodal microblog using co-attention network. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, 19–25 August 2017, pp. 3420–3426 (2017)
22.
go back to reference Zhou, B., Lapedriza, À., Xiao, J., Torralba, A., Oliva, A.: Learning deep features for scene recognition using places database. In: Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, Montreal, Quebec, Canada, 8–13 December 2014, pp. 487–495 (2014) Zhou, B., Lapedriza, À., Xiao, J., Torralba, A., Oliva, A.: Learning deep features for scene recognition using places database. In: Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, Montreal, Quebec, Canada, 8–13 December 2014, pp. 487–495 (2014)
Metadata
Title
Hashtag Recommendation with Attention-Based Neural Image Hashtagging Network
Authors
Gaosheng Wu
Yuhua Li
Wenjin Yan
Ruixuan Li
Xiwu Gu
Qi Yang
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-030-04179-3_5

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