梁上松

教师简介: 

Bio：Shangsong Liang is currently 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 Information Retrieval, Data Mining, Artificial Intelligence and Deep Learning. He has published over 120 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 2017-2021、KDD 2021、ICML 2021、NeurIPS 2020、WWW 2018-2021、IJCAI 2018-2021 (IJCAI 2021 SPC)、WSDM 2018-2021、AAAI 2019-2021, and served as reviewer for a number of conferences and journals such as SIGIR 2014-2021, CIKM 2015-2021, ACL 2016-2021, AAAI 2017-2021, WSDM 2018-2021, WWW 2018-2021, AAAI 2019-2021, WSDM 2019-2021, 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, Information Retrieval, 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

代表性论著: 

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

Selected Publications:

122. Muhammad Arslan Manzoor, Ruihong Zeng, Dilshod Azizov, Preslav Nakov, and Shangsong Liang. MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media. 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL), 2025. To appear.

121. Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G Honavar SimPER: Simple Preference Fine-Tuning without Hyperparameters by Perplexity Optimization. Twenty-first International Conference on Learning Representations (ICLR), 2025. To appear.

120. Guoming Li, Jian Yang, Shangsong Liang, Dongsheng Luo. Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices Approach. In Proceedings of the ACM Web Conference (WWW), 2025. To appear.

119. Guoming Li, Jian Yang, Shangsong Liang. ERGNN: Spectral Graph Neural Network with Explicitly-optimized Rational Graph Filters. The 2025 International Conference on Acoustics, Speech, and Signal Processing, ICASSP, 2025. To appear.

118. Lingyue Hu, Kailong Zhao, Bingo Wing-Kuen Ling, Shangsong Liang, Yiting Wei. Improving Human Activity Recognition via Graph Attention Network with Linear Discriminant Analysis and Residual Learning. Biomedical Signal Processing and Control, 2025.

117. Yanfang Ling, Jiyong Li, Lingbo Li, Shangsong Liang. Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing. Advances in Neural Information Processing Systems, NeurIPS, 2024

116. Dilshod Azizov, Zain Muhammad Mujahid, Hilal AlQuabeh, Preslav Nakov, Shangsong Liang. SAFARI: Cross-lingual Bias and Factuality Detection in News Media and News Articles. The 2024 conference on Empirical Methods in Natural Language Processing, EMNLP Findings, 2024. 

115. Ruihong Zeng, Jinyuan Fang, Siwei Liu, Zaiqiao Meng, and Shangsong Liang. Enhancing Graph Neural Networks via Memorized Global Information. ACM Transactions on the Web, TWEB, 2024.

114. Shangsong Liang, Zhou Pan, Wei Liu, and Jian Yin. A Survey on Variational Autoencoders in Recommender Systems. ACM Computing Surveys, 2024.

113. Jiahang Cao, Jinyuan Fang, Zaiqiao Meng, and Shangsong Liang. Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces. ACM Computing Surveys, 2024. 

112. Guanzheng Chen, Xin Li, Zaiqiao Meng, Shangsong Liang, Lidong Bing. CLEX: Continuous Length Extrapolation for Large Language Models. Twelfth International Conference on Learning Representations, ICLR, 2024. 

111. Jiyong Li, Dilshod Azizov, Yang Li, and Shangsong Liang. Contrastive Continual Learning with Importance Sampling and Prototype-Instance. Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI, 2024. 

110. Liang Li, Qisheng Liao, Meiting Lai, Di Liang, and Shangsong Liang. Local and Global: Text Matching via Syntax Graph Calibration. IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, 2024. 

109. Changsheng Ma, Taicheng Guo, Qiang Yang, Xiuying Chen, Xin Gao, Shangsong Liang, Nitesh Chawla, and Xiangliang Zhang. A Property-Guided Diffusion Model for Generating Molecular Graphs. IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, 2024. 

108. Weiwei Yang, Shangsong Liang, Jian Yin. Spatial-Aware Multi-Directional Autoencoder For Pre-Training. The Computer Journal, 67(4):1346-1360, 2024.

107. Wei Liu, Shangsong Liang, Huajie Zhu, Leong Hou U, Jianxing Yu, Xiang Li, and Jian Yin. Variational Kernel Density Estimation Recommendation Algorithm for Users with Different Activity Level.  In Proceedings of the International Conference on Database Systems for Advanced Applications DASFAA, pp. 1-16, 2024.

106. Wei Liu, Leong Hou U, Shangsong Liang, Huaijie Zhu, Jianxing Yu, Yubao Liu, Jian Yin. VAE*: A Novel Variational Autoencoder via Revisiting Positive and Negative Samples for Top-N Recommendation. ACM Transactions on Knowledge Discovery from Data, TKDD, 2024.

105. Jiachen Yu, Yuehong Wu, Shangsong Liang. Wasserstein Topology Transfer for Joint Distilling Embeddings of Knowledge Graph Entities and Relations. International Conference on Algorithms, Computing and Artificial Intelligence, 176-182, 2024.

106. Zaiqiao Meng, Shangsong Liang, Xin Xin, Gianluca Moro, Evangelos Kanoulas, Emine Yilmaz. KEIR@ ECIR 2024: The First Workshop on Knowledge-Enhanced Information Retrieval. ECIR, 2024.

104. Zhaohan Meng, Siwei Liu, Shangsong Liang, Bhautesh Jani, Zaiqiao Meng. Heterogeneous biomedical entity representation learning for gene–disease association prediction. Briefings in Bioinformatics, 2024.

103. Zhaopeng Yang, Huan Hao, Shangsong Liang. ACTOR: Adapting CLIP for Fully Transformer-based Open-vocabulary Detection. In Proceedings of the 2024 International Conference on Generative Artificial Intelligence and Information Security, 2024.

102. Huaiwen He, Xiangdong Yang, Feng Huang, Feng Yi, Shangsong Liang. GAT4Rec: Sequential Recommendation with a Gated Recurrent Unit and Transformers. Mathematics, vol. 12, issue 14, 2024.

101. Ming Qin, Xun Li, Yuhao Wang, Zhenping Li, Hongbin Ye, Zongbing Wang, Weihao Gao, Shangsong Liang, Qiang Zhang, Keyan Ding. ProTeM: Unifying Protein Function Prediction via Text Matching. International Conference on Artificial Neural Networks, 2024.

100. Jiasheng Li, Zaiqiao Meng, Shangsong Liang. Towards Deep Generative Backmapping of Coarse-Grained Molecular Systems. The 2024 Asia Conference on Computer Vision, Image Processing and Pattern Recognition, 2024.

99. Ming Qin, Xun Li, Yuhao Wang, Zhenping Li, Hongbin Ye, Zongbing Wang, Weihao Gao, Shangsong Liang, Qiang Zhang, Keyan Ding. ProTeM: Unifying Protein Function Prediction via Text Matching. The International Conference on Artificial Neural Networks, 2024.

98. Junjian Lu, Siwei Liu, Dmitrii Kobylianskii, Etienne Dreyer, Eilam Gross, and Shangsong Liang. PASCL: supervised contrastive learning with perturbative augmentation for particle decay reconstruction. Machine Learning: Science and Technology, 2024.

97. Yuehong Wu, Zhiwei Wen, Shangsong Liang. Predicting Question Popularity for Community Question Answering. Electronics, 2024.

95. Jiyong Lee, Dilshod Azizov, and Shangsong Liang. Lotus at WojoodNER Shared Task: Multilingual Transformers: Unveiling Flat and Nested Entity Recognition. Arabic Natural Language Processing Conference, ArabicNLP 2023. 

94. Dilshod Azizov, Jiyong Lee, and Shangsong Liang. Frank at ArAIEval Shared Task: Arabic Disinformation and Persuasion: Power of Pretrained Models. Arabic Natural Language Processing Conference, ArabicNLP 2023. 

93. Dilshod Azizov, Jiyong Lee, and Shangsong Liang. Frank at NADI 2023 Shared Task: Trio-based Ensemble Approach for Arabic Dialect Identification. Arabic Natural Language Processing Conference, ArabicNLP 2023.

92. Jiahang Cao, Jinyuan Fang, Zaiqiao Meng, and Shangsong Liang. Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces. ACM Computing Surveys, 2023. 

91. Changsheng Ma, Qiang Yang, Shangsong Liang, and Xin Gao. A Distribution Preserving Model for Molecular Graph Generation. IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM, 2023. 

90. Dilshod Azizov, Jiyong Li, Hilal AlQuabeh, and Shangsong Liang. Advanced NLP Techniques for Summarizing Multilingual Financial Narratives from Global Annual Reports. In the 5th Financial Narrative Processing Workshop (FNP 2023) of the IEEE International Conference on Big Data, 20203.

89. Muhammad Arslan Manzoor, Sarah Albarri, Ziting Xian, Zaiqiao Meng, Preslav Nakov, and Shangsong Liang. Multimodality Representation Learning: A Survey on Evolution, Pretraining and Its Applications. ACM Transactions on Multimedia Computing, Communications, and Applications, 2023.

88. Xiaoru Chen, Yingxu Wang, Jinyuan Fang, Zaiqiao Meng, and Shangsong Liang. Heterogeneous Graph Contrastive Learning with Metapath-based Augmentations. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023.

87. Jingjie Wang, Shiyang Liang, Siwei Liu, Junliang Song, Qiang Lin, Shihong Zhao, Shuaixin Li, Jiahui Li, Shangsong Liang. HMCDA: A Novel Method Based on the Heterogeneous Graph Neural Network and Metapath for CircRNA-Disease Associations Prediction. BMC Bioinformatics, 2023.

86. Zixiao Wang, Shiyang Liu, Siwei Liu, Zhaohan Meng, Jingjie Wang, and Shangsong Liang. Sequence Pre-training-based Graph Neural Network for Predicting lncRNA-miRNA Associations. Briefings in Bioinformatics, 2023. 

85. Dilshod Azizov, Preslav Nakov, and Shangsong Liang. Frank at CheckThat! 2023: Detecting the Political Bias of News Articles and News Media. In CLEF 2023.

84. Shangsong Liang, Shaowei Tang, Zaiqiao Meng, and Qiang Zhang. Cross-Temporal Snapshot Alignment for Dynamic Networks. IEEE Transactions on Knowledge and Data Engineering, 35(3), pp. 2406-2420, 2023.

83. Yingxu Wang, Xiaoru Chen, Jinyuan Fang, Zaiqiao Meng, and Shangsong Liang. Enhancing Conversational Recommendation Systems with Representation Fusion. ACM Transactions on the Web, 6:1-6:34, 2023.

82. Wei Liu, Leong Hou U, Shangsong Liang, Huajie Zhu, Jianxing Yu, Yubao Liu, and Jian Yin. Revisiting Positive and Negative Samples in Variational Autoencoders for Top-N Recommendation. DASFAA (2), pp. 562-573, 2023.

81. Bin Wu, Jinyuan Fang, Xiangxiang Zeng, Shangsong Liang, Qiang Zhang. Adaptive Compositional Continual Meta-Learning. International Conference on Machine Learning, ICML 2023. Full paper. 2023.

80. Zhengyu Hu, Jieyu Zhang, Haonan Wang, Siwei Liu, and Shangsong Liang. Leveraging Relational Graph Neural Network for Transductive Model Ensemble.  In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2023, USA., 2023. Full paper.

79. Tianjun Yao, Yingxu Wang, Kun Zhang, and Shangsong Liang. Improving the Expressiveness of K-hop Message-Passing GNNs by Injecting Contextualized Substructure Information. In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2023, USA., 2023. Full paper.

78. Zhiyong Xiong, Zhaoxiong Yan, Huanan Yao, and Shangsong Liang. Design Demand Trend Acquisition Method Based on Short Text Mining of User Comments in Shopping Websites. Information, 13(3):110, 2022.

77. Shaowei Tang, Zaiqiao Meng, and Shangsong Liang. Dynamic Co-embeddinig Model for Temporal Attributed Networks. IEEE Transactions on Neural Networks and Learning Systems. 2022.

76. Bin Wu, Zaiqiao Meng, Qiang Zhang, and Shangsong Liang. Meta-Learning Helps Personalized Product Search. In Proceedings of the ACM Web Conference, WWW 2022, pp. 2277-2287, 2022.

75. Guanzheng Chen, Fangyu Liu, Zaiqiao Meng, and Shangsong Liang. Revisiting Parameter-Efficient Tuning: Are We Really There Yet? In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022. Full paper, 2022.

74. Bin Wu, Shangsong Liang, and Yuehong Wu. Data-Hungry Issue in Personalized Product Search. 2022.

73. Lvjia Chen, and Shangsong Liang. Cross-Temporal Snapshot Alignment for Dynamic Multi-Relational Networks. Journal of Physics: Conference Series 2253 (1), 2022.

72. Bin Wu, Zaiqiao Meng, Qiang Zhang, and Shangsong Liang.  Meta-Learning Helps Personlized Product Search, The Web Conference, WWW 2022. Full paper. pp. 2277-2287, 2022.

71. Guanzheng Chen, Jinyuan Fang, Zaiqiao Meng, Qiang Zhang, and Shangsong Liang.  Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network, Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022. Full paper, 2022.

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.