梁上松

教师简介: 

Bio：Shangsong Liang is an associate professor at the School of Computer Science, Sun Yat-sen University, Guangzhou, China. He received a Ph.D. degree from the University of Amsterdam, The Netherlands, in 2014, supervised by Prof. dr. Maarten de Rijke, Academician of the Royal Netherlands Academy of Arts and Sciences, in the field of computer science. His research interests lie in the field of Natural Language Processing, Information Retrieval, Data Mining, Artificial Intelligence and Deep Learning. He has published a number of peer-reviewed papers, most of which are in top-tier venues such as SIGIR, KDD, WSDM, AAAI, CIKM, ECIR, IEEE TKDE, ACM TOIS and Information Processing & Management. He is an editor members of Information Processing & Management since 2016 and Journal of Computer Science and Technology sinice 2021, and an editor for Frontiers in ICT and Frontiers in Computer Science sinice October 2021. He is PC member in a number of conferences such as SIGIR、KDD、ICML、NeurIPS、WWW、IJCAI (IJCAI 2021 SPC)、WSDM、AAAI, and served as reviewer for a number of conferences and journals such as SIGIR, CIKM, ACL, AAAI, WSDM, WWW, AAAI, WSDM, ACM TOIS, ACM trans. on the Web, IP&M, Information Retrieval. He received various awards/honors such as the SIGIR 2017 Outstanding Reviewer Award, Outstanding Contribution for instructing Data Mining course from the International Petroleum Engineers, the Kingdom of Saudi Arabia Section. 

Research Interests: Information Retrieval, Data Mining, Artificial Intelligence and Machine Learning

研究领域: 

自然语言处理、信息检索、机器学习、人工智能

Research Interests

Natural Language Processing, Data Analytics, Information Retrieval, Data Mining, Machine Learning (Deep Learning), Artificial Intelligence 

学习经历: 

2011.9-2014.12，荷兰阿姆斯特丹大学，博士，导师：Maarten de Rijke院士

Education Experience

2011.9-2014.12, University of Amsterdam，PhD student

教授课程: 

人工智能、数据挖掘导论、信息检索、机器学习与数据挖掘

Teaching

Natural Language Processing, Artificial Intelligence, Introduction to Data Mining, Information Retrieval, Machine Learning and Data Mining, Data Analytics and Evaluation

代表性论著: 

出版物 (其中NeurIPS (NIPS)、ICML, KDD、SIGIR、WWW、ACL、AAAI、IJCAI、TKDE、TOIS、ACM Computing Survey等为CCF A类为国际顶级会议/期刊，WSDM、EMNLP、CIKM、RecSys、TKDD、TWEB、IPM等为CCF B类国际著名会议/期刊)：

Selected Publications:

更多已出版著作，请至 谷歌学术

For more publications, please go to the Google Scholar: https://scholar.google.com/citations?user=4uggVcIAAAAJ&hl=en

70. Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, and Shangsong Liang. Structure-Aware Random Fourier Kernel for Graphs, Neural Information Processing Systems 2021, NeurIPS 2021. Full paper. 2021.

69. Qiang Zhang, Jinyuan Fang, Zaiqiao Meng, Shangsong Liang, and Emine Yilmaz. Variational Continual Bayesian Meta-Learning. Neural Information Processing Systems 2021, NeurIPS 2021. Full paper. 2021.

68. Shangsong Liang, Yupeng Luo, and Zaiqiao Meng. Profiling Users for Question Answering Communities via Flow-based Constrained Co-embedding Model.  ACM Transactions on Information Systems (TOIS), 2021.

67. Shangsong Liang, Zhuo Ouyang, and Zaiqiao Meng. A Normalizing Flow-based Co-embedding Model for Attributed Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2021.

66. Jinyuan Fang, Shangsong Liang, Zaiqiao Meng, and Maarten de Rijke. Hyperspherical Variational Co-embedding for Attributed Networks. ACM Transactions on Information Systems (TOIS), 2021.

65. Yaoxin Pan, Zaiqiao Meng, Shangsong Liang. Personalized, Sequential, Attentive, Metric-Aware Product Search. ACM Transactions on Information Systems (TOIS), 2021.

64. Shangsong Liang, Shaowei Tang, Zaiqiao Meng, and Qiang Zhang. Cross-Temporal Snapshot Alignment for Dynamic Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE). 2021.

63. Lu Yu, Shichao Pei, Chuxu Zhang, Bai Xiao, Shangsong Liang, Nitesh Chawla, and Xiangliang Zhang et al. Addressing Class-Imbalance Problem for Personalized Ranking. ACM Transactions on Information Systems (TOIS), 2021.

62. Xiaofei Zhu, Ling Zhu, Jiafeng Guo, Shangsong Liang, and Stefan Dietze. Global and Local Dependency Guided Graph Convolutional Networks for Aspect-based Sentiment Classification. Expert Systems With Applications. 2021.

61. Yadong Zhu, Xiliang Wang, ing Li, Tianjun Yao, and Shangsong Liang. BotSpot++: A Hierarchical Deep Ensemble Model for Bots Install Fraud Detection in Mobile Advertising. ACM Transactions on Information Systems (TOIS). 2021.

60. Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, and Shangsong Liang. Gaussian Process with Graph Convolutional Kernel for Relational Learning. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021, Singapore, 2021. Full paper. 

59. Senhong Wang, Jianzhou Cao, Fangyuan Lei, Qingyun Dai, Shangsong Liang, Bingo Wing-Kuen Ling. Semi-supervised Multi-View Clustering with Weighted Anchor Graph Embedding. Computational Intelligence and Neuroscience, 2021. 

58. Zhiyong Xiong, Zhaoxiong Yan, Huanan Yao, Shangsong Liang. Design Demand Trend Acquisition Method based on Short Text Mining of User Comments in Shopping Websites. Information, Accepted subject to major revisions, 2021.

57. Xiaopeng Chao, Jiangzhong Cao, Yuqin Lu, Qingyun Dai, Shangsong Liang. Constrained Generative Adversarial Networks. IEEE Access 9: 19208-19218, 2021.

56. Siyuan Liao, Shangsong Liang, Zaiqiao Meng and Qiang Zhang. Learning Dynamic Embeddings for Temporal Knowledge Graphs. The 29th ACM International Conference on Web Search and Data Mining, WSDM 2021. Full paper. 

55. Liangliang Ma, Hong Shen, Shangsong Liang. A Novel Distributed Reinforcement Learning Method for Classical Chinese Poetry Generation. The 21st International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2020. Full paper.

54. Tianjun Yao, Qing Li, Shangsong Liang, and Yadong Zhu. BotSpot: A Hybrid Learning Framework to Uncover Bot Install Fraud in Mobile Advertising. The 29th ACM International Conference on Information and Knowledge Management, CIKM 2020. Full paper. 

53. Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis, Shangsong Liang, Siwei Liu, Guangtao Zeng, Liang Junha, Yucheng Liang, Qiang Zhang, Yaxiong Wu. BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. The 14th ACM Conference on Recommender Systems (RecSys 2020), Sep 2020. Demo paper. 

52. Huimin Huang, Zaiqiao Meng, Shangsong Liang. Recurrent Neural Variational Model for Follower-based Influence Maximization. Information Sciences. 2020. 

51. Zaiqiao Meng, Shangsong Liang, Xiangliang Zhang, Richard McCreadie and Iadh Ounis. Jointly Learning Representations of Nodes and Attributes for Attributed Networks. ACM Transactions on Information Systems (TOIS), Regular paper, 2020. 

50. Zaiqiao Meng, Shangsong Liang, Jinyuan Fang and Teng Xiao. Semi-supervisedly Co-embedding Attributed Networks. Neural Information Processing Systems 2019, NeurIPS 2019. Full paper. 

49. Yupeng Luo, Shangsong Liang, and Zaiqiao Meng. Constrained Co-embedding for User Profile in Community Question Answering. The 28th ACM International Conference on Information and Knowledge Management, CIKM 2019. Full paper. 

48. Teng Xiao, Shangsong Liang, and Zaiqiao Meng. Dynamic Collaborative Recurrent Learning. The 28th ACM International Conference on Information and Knowledge Management, CIKM 2019. Full paper. 

47. Teng Xiao (co-first author), Zaiqiao Meng, Huan Sun, and Shangsong Liang. Dynamic Bayesian Metric Learning for Personalized Product Search. The 28th ACM International Conference on Information and Knowledge Management, CIKM 2019. Full paper. 

46. Jing Song, Hong Shen, Zijing Ou , Junyi Zhang , Teng Xiao, and Shangsong Liang. BISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation. The 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Full paper. 

45. Qiang Zhang, Shangsong Liang, Aldo Lipani, Zhaochun Ren, and Emine Yilmaz. From Stances’ Imbalance to their Hierarchical Representation and Detection. In Proceedings of the 28th International World Wide Web Conference,  WWW 2019, San Francisco, 2019. Full paper. 

44. Qiang Zhang, Aldo Lipani, Shangsong Liang, and Emine Yilmaz. Reply-aided Detection of Misinformation via Bayesian Deep Learning. In Proceedings of the 28th International World Wide Web Conference,  WWW 2019, San Francisco, 2019. Full paper. 

43. Shangsong Liang. Unsupervised Semantic Generative Adversarial Networks for Expert Retrieval. In Proceedings of the 28th International World Wide Web Conference,  WWW 2019, San Francisco, 2019. Full paper. 

42. Xiao Teng, Shangsong Liang, and Zaiqiao Meng. Hierarchical Neural Variational Model for Personalized Sequential Recommendation. In Proceedings of the 28th International World Wide Web Conference,  WWW 2019, San Francisco, 2019. Short paper.  

41. Zaiqiao Meng, Shangsong Liang, Hongyan Bao, Xiangliang Zhang. Co-embedding Attributed Networks. 12th ACM International Conference on Web Search and Data Mining (WSDM), 2019. Full paper. 

40. Teng Xiao (master student), Shangsong Liang, Weizhou Shen, Zaiqiao Meng. Bayesian Deep Collaborative Matrix Factorization. Thirty-third AAAI Conference on Artificial Intelligence (AAAI), 2019. Full paper. 

39. Lu Yu (PhD student), Chuxu Zhang, Shangsong Liang, Xiangliang Zhang. Multi-order Attentive Ranking Model for Sequential Recommendation. Thirty-third AAAI Conference on Artificial Intelligence (AAAI), 2019. Full paper. 

38. Shangsong Liang, Emine Yilmaz, Evangelos Kanoulas. Collaboratively Tracking Interests for User Clustering in Streams of Short Texts. IEEE transactions on Knowledge and Data Engineering (TKDE), 31(2), pp. 257-272, 2019. 

37. Shangsong Liang. Collaborative, Dynamic and Diversified User Profiling. Thirty-third AAAI Conference on Artificial Intelligence (AAAI), 2019. Full paper. 

36. Qiang Zhang (PhD student), Shangsong Liang, Emine Yilmaz. Variational Self-attention Model for Sentence Representation. The third NeurIPS Workshop on Bayesian Deep Learning at NIPS 2018.  2018.

35. Shangsong Liang, Xiangliang Zhang, Zhaochun Ren, Evangelos Kanoulas. Dynamic Embeddings for User Profiling in Twitter. Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018, London, United Kingdom, 2018. Full paper. 

34. Shangsong Liang, Ilya Markov, Zhaochun Ren, Maarten de Rijke. Manifold Learning for Rank Aggregation. The 27th International Web conference (WWW), 2018. Full paper. April, 2018. pp. 1735-1744, Full paper. 

33. Shangsong Liang. Dynamic User Profiling for Streams of Short Texts. Thirty- second AAAI Conference on Artificial Intelligence (AAAI), pp. 5860-5867, 2018. Full paper. 

32. Shangsong Liang, Zhaochun Ren, Jun Ma, Emine Yilmaz, Maarten de Rijke. Inferring Dynamic User Interests in Streams of Short Texts for User Clustering. ACM Transactions on Information Systems (TOIS), Vol. 36, No. 1, Article 10, pp. 1-36, 2017. 

31. Shangsong Liang, Emine Yilmaz, Hong Shen, Maarten de Rijke, W. Bruce Croft. Search Result Diversification in Short Text Streams. ACM Transactions on Information Systems (TOIS), Vol. 36, No. 1, pp. 1-35, 2017. 

30. Shangsong Liang, Zhaochun Ren, Emine Yilmaz, Evangelos Kanoulas. Collabor- ative User Clustering for Short Text Streams. Thirty-First AAAI Conference on Artificial Intelligence (AAAI), pp. 3504-3510, 2017. Full paper. 

29. Shangsong Liang, Emine Yilmaz, Evangelos Kanoulas. Dynamic Clustering of Streaming Short Documents. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2016), pp. 995-1004, San Francisco, U.S.A, 2016. Full paper. 

28. Shangsong Liang, Fei Cai, Zhaochun Ren, Maarten de Rijke. Efficient Structured Learning for Personalized Diversification. IEEE transactions on Knowledge and Data Engineering (TKDE), Vol. 28, No. 11, pp. 2958–2973, 2016. 

27. Shangsong Liang (co-first author), Yukun Zhao, Zhaochun Ren, Jun Ma, Emine Yilmaz, Maarten de Rijke. Explainable User Clustering in Short Text Streams. Proceedings of the 39th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2016), pp. 155-164, Pisa, Tuscany, Italy, 2016. Full paper.

26. Shangsong Liang. Fusion and Diversification in Information Retrieval. University of Amsterdam Press, ISBN: 978-94-6182-522-3, pp. 182, December, 2014.

25. Shangsong Liang, Zhaochun Ren, Maarten de Rijke. Personalized Search Result Diversification via Structured Learning. Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2014), pp. 751-760, New York, U.S.A, 2014. Full paper. 

24. Shangsong Liang, Zhaochun Ren, Maarten de Rijke. Fusion Helps Diversification. Proceedings of the 37th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2014), pp. 303-312, Gold Coast, Australia, 2014. Full paper. 

23. Shangsong Liang, Maarten de Rijke. Finding Knowledgeable Groups in Enterprise Corpora. In Proceedings of the 36th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2013), pp. 1005-1008, Dublin, Ireland, 2013. 

22. Shangsong Liang, Maarten de Rijke. Formal language Models for Finding Groups of Experts. Information Processing & Management (IPM), Vol. 52, No. 4, pages 529- 549, 2016. 

21. Shangsong Liang, Maarten de Rijke. Burst-Aware Data Fusion for Microblog Search. Information Processing & Management (IPM), Vol. 51, pages. 89-113, Elsevier, 2015. 

20. Shangsong Liang, Zhaochun Ren, Wouter Weerkamp, Edgar Meij, Maarten de Rijke. Time-Aware Rank Aggregation for Microblog Search. Proceedings of the 23rd Inter-national ACM Conference on Information and Knowledge Management (CIKM 2014), pp. 989-998, Shanghai, China, 2014. Full paper. 

19. Shangsong Liang (co-first author), Hongya Song (co-first author), Zhaochun Ren (co-first author), Piji Li, Jun Ma, Maarten de Rijke. Summari-zing Answers in Non-Factoid Community Question-Answering. In The Tenth ACM International Conference on Web Search and Data Mining (WSDM 2017), pp. 405-414, Cambridge, U.K., 2017. Full paper. 

18. Shangsong Liang, Zhaochun Ren, Maarten de Rijke. The Impact of Semantic Document Expansion on Cluster-based Fusion for Microblog Search. In Proceedings of the 36th European Conference on Information Retrieval (ECIR 2014), pp. 493-499, Amsterdam, The Netherlands, 2014. Full paper. 

17. Shangsong Liang, Maarten de Rijke, Manos Tsagkias. Late Data Fusion for Microblog Search. In Proceedings of the 35th European Conference on Information Retrieval (ECIR 2013), Moscow, Russia, 2013. Short paper. 

16. Shangsong Liang, Dongjian He. Image Classification Using Compound Image Transfor-mations, Multi-Class SVM. ICIC Express Letters, An International Journal of Research and Surveys, Volume 6, Issue 3, March 2012.

15. Xisen Jin, Wenqiang Lei, Hongshen Chen, Shangsong Liang, Zhaochun Ren, Yihong Zhao, Dawei Yin. Explicit State Tracking with Semi-supervision for Neural Dialogue Generation, Proceedings of the 23rd Inter-national ACM Conference on Information and Knowledge Management (CIKM 2018), Shanghai, China, 2018. Full paper. 

14. Qiang Zhang, Emine Yilmaz, Shangsong Liang. Ranking-based Method for News Stance Detection. Proceedings of the 27th The Web Conference (WWW 2018), Lyon, France. Poster. 

13. Zhaochun Ren, Shangsong Liang, Piji Li, Shuaiqiang Wang, Maarten de Rijke. Social Collaborative Viewpoint Regression with Explainable Recommendations. The Tenth ACM International Conference on Web Search and Data Mining (WSDM 2017). Cambridge, U.K., 2017. Full paper. 

12. Bin Zhou, Vasileios Lampos, Shangsong Liang, Zhaochun Ren, Emine Yilmaz, Ingemar Cox. A Concept Language Model for Ad-Hoc Search. Proceedings of the 26th International World Wide Web Conference (WWW 2017), Montréal, Canada, 2017. Short paper. 

11. Fei Cai, Shangsong Liang, Maarten de Rijke. Prefix-adaptive and Time-sensitive Personalized Query Auto Completion. 2016. IEEE transactions on Knowledge and Data Engineering (TKDE). 

10. Yukun Zhao, Shangsong Liang, Jun Ma. Personalized Re-Ranking of Tweets. In Proceedings of the 17th International Conference on Web Information System Engineering (WISE 2016), Shanghai, China, 2016. Full paper. 

9. Zhaochun Ren, Hongya Song, Piji Li, Shangsong Liang, Jun Ma, and Maarten de Rijke. Using Sparse Coding for Answer Summarization in Non-Factoid Community Question-Answering. In WebQA 2016 —SIGIR 2016: Web Question Answering, Beyond Factoids. ACM, July 2016. Full paper.

8. Fei Cai, Shangsong Liang, Maarten de Rijke. Personalized Document Re-ranking Based on Bayesian Probabilistic Matrix Factorization. Proceedings of the 37th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2014), Gold Coast, Australia, 2014. Short paper. 

7. Fei Cai, Shangsong Liang, Maarten de Rijke. Time-Sensitive Personalized Query Auto-Completion. Proceedings of the 23rd International ACM Conference on Information and Knowledge Management (CIKM 2014), Shanghai, China, 2014. Full paper. 

6. Zhaochun Ren, Maria-Hendrike Peetz, Shangsong Liang, Maarten de Rijke. Hierarchical multi-label classification of social text streams. In Proceedings of the 37th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2014), Gold Coast, Australia, 2014. Full paper. 

5. Zhaochun Ren, Shangsong Liang, Edgar Meij, Maarten de Rijke. Personalized Time-aware Tweets Summarization. In Proceedings of the 36th International ACM Conference on Research and Development in Information Retrieval (SIGIR 2013), Dublin, Ireland, 2013. Full paper. 

4. Wouter Weerkamp, Richard Berendsen, Shangsong Liang, Zhaochun Ren, Manos Tsagkias, Nikos Voskarides. The University of Amsterdam (ILPS) at TREC 2013 Microblog Track. In Proceedings of the 22nd Text Retrieval Conference (TREC 2013), National Institute of Standard and Technology, U.S.A, 2013. Full paper. 

3. Hang Zhang, Paul Yanne, Shangsong Liang. Plant Species Classification Using Leaf Shape and Texture. In Proceedings of the IEEE Conference on Industrial Control and Electronics Engineering. Xi’an, China, 2012. Full paper.

2. Dongjian He, Shangsong Liang*, Yong Fang. A Multi- Descriptor, Multi-Nearest Neighbor Approach for Image Classification. In Proceedings of Sixth International Conference on Intelligent Computation (ICIC 2010). Changsha, China, 2010. Full paper.

1. Jinglei Tang, Xu Jing, Dongjian He, Shangsong Liang. Blind-Road Location and Recognition in Natural Scene. In World Congress on Computer Science and Information Engineering. Los Angeles, California, U.S.A, 2009. Full paper.