User Conditional Hashtag Recommendation for Micro-Videos

When a user tend to publish a micro-video, hashtag recommendation aims to suggest hashtags that can reflect the theme or contents of the micro-video, and meet the user tagging preference as well. In this paper, we show how user profile and historical hashtags combined with micro-video representations can be used to perform hashtag recommendation. Specifically, a User-guided Hierarchical Multi-head Attention Network (UHMAN) is proposed to attend both image-level and video-level representations of micro-videos with user side information. We evaluate the proposed model on the dataset collected from micro-video sharing platform Musical.ly. The experimental results demonstrate the effectiveness of the proposed method.

[1]  Jie Yan,et al.  Correlation identification in multimodal weibo via back propagation neural network with genetic algorithm , 2019, J. Vis. Commun. Image Represent..

[2]  Lars Schmidt-Thieme,et al.  Personalized Tag Recommendation for Images Using Deep Transfer Learning , 2017, ECML/PKDD.

[3]  Roelof van Zwol,et al.  Flickr tag recommendation based on collective knowledge , 2008, WWW.

[4]  Jason Weston,et al.  WSABIE: Scaling Up to Large Vocabulary Image Annotation , 2011, IJCAI.

[5]  Feng Xu,et al.  Hashtag Recommendation for Photo Sharing Services , 2019, AAAI.

[6]  Emily Denton,et al.  User Conditional Hashtag Prediction for Images , 2015, KDD.

[7]  Zhenzhong Chen,et al.  User-Video Co-Attention Network for Personalized Micro-video Recommendation , 2019, WWW.

[8]  Lei Zhu,et al.  Personalized Hashtag Recommendation for Micro-videos , 2019, ACM Multimedia.

[9]  Apostol Natsev,et al.  Collaborative Deep Metric Learning for Video Understanding , 2018, KDD.

[10]  Wray L. Buntine,et al.  Topic Model : Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon , 2014 .

[11]  Jason Weston,et al.  #TagSpace: Semantic Embeddings from Hashtags , 2014, EMNLP.

[12]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Xuanjing Huang,et al.  Hashtag Recommendation for Multimodal Microblog Using Co-Attention Network , 2017, IJCAI.

[14]  Alex Graves,et al.  Recurrent Models of Visual Attention , 2014, NIPS.

[15]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[16]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.