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Zili Zhou

PhD Candidate of Advanced Analytics Institute, University of Technology Sydney.


Zili Zhou is currently a PhD candidate of School of Software, Faculty of Engineering & IT, University of Technology Sydney. His research interests include knowledge graph representation learning, knowledge inference and knowledge graph application.

Publications

Zhou, Z., Xu, G., Zhu, W., Li, J., & Zhang, W. (2017, May). Structure embedding for knowledge base completion and analytics. In Neural Networks (IJCNN), 2017 International Joint Conference on (pp. 737-743). IEEE. (International Joint Conference on Neural Networks (IJCNN 2017), Anchorage, Alaska, USA, 14 May 2017 - 19 May 2017.   2017https://opus.lib.uts.edu.au/handle/10453/111108

Zhou, Z., Xu, G., Zhu, X., & Liu, S. (2017, October). Latent factor analysis for low-dimensional implicit preference prediction. In Behavioral, Economic, Socio-cultural Computing (BESC), 2017 International Conference on (pp. 1-2). IEEE. (International Conference on Behavioral, Economic, and Socio-Cultural Computing, Poland, 16 Oct 2017 - 18 Oct 2017.   IEEE. 15 Janhttps://opus.lib.uts.edu.au/handle/10453/122322

Liu, S., Xu, G., Zhu, X., & Zhou, Z. (2017, October). Towards simplified insurance application via sparse questionnaire optimization. In Behavioral, Economic, Socio-cultural Computing (BESC), 2017 International Conference on (pp. 1-2). IEEE. (International Conference on Behavioral, Economic, and Socio-Cultural Computing, Poland, 16 Oct 2017 - 18 Oct 2017.   IEEE. 15 Janhttps://opus.lib.uts.edu.au/handle/10453/122321

Zhou, Z., Liu, S., Xu, G., Xie, X., Yin, J., Li, Y., & Zhang, W. (2018, June). Knowledge-Based Recommendation with Hierarchical Collaborative Embedding. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 222-234). Springer, Cham. https://opus.lib.uts.edu.au/handle/10453/123208
 
Yin, J., Zhou, Z., Liu, S., Wu, Z., & Xu, G. (2018, June). Social Spammer Detection: A Multi-Relational Embedding Approach. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 615-627). Springer, Cham. https://opus.lib.uts.edu.au/handle/10453/126027