Publications

Books, Edited Books and Book Chapters

  1. G. Xu, Y Zong and Z. Yang, Applied Data Mining, CRC/Taylor&Francis Press, June 17, 2013, 284 Pages
  2. G. Xu and L. Li, Social Media Mining and Social Network Analysis: Emerging Research (Eds), IGI-Global, January 2013
  3. T. Luo, S. Chen, G. Xu, J. Zhou, Trust-based Collective View Prediction, 2013 by Springer, 146 Pages
  4. G. Xu, Y. Zhang, L. Li, Web Mining and Social Networking: Techniques and Applications, Springer, 2010
  5. G. Xu, Z. Wu, J. Cao, H. Tao, Models for Community Dynamics, in book: Encyclopedia of Social Network Analysis and Mining 2014: 969-982
  6. G. Xu, Y. Gu, and X. Yi, On Group Extraction and Fusion for Tag-Based Social Recommendation, in book: Social Media Mining and Social Network Analysis: Emerging Research (Chapter 14), Pages 211-223, 2012
  7. Y. Zong, G. Xu, Clustering Algorithms for Tags, in book: Social Media Mining and Social Network Analysis: Emerging Research (Chapter 3), Pages 39-53, 2012
  8. L Li, H. Xiao, G. Xu, Recommending Related Microblogs, in book: Social Media Mining and Social Network Analysis: Emerging Research (Chapter 13), Pages 202-210, 2012
  9. G. Xu, Building User Communities of Interests by Using Latent Semantic Analysis, in book: Collaborative Search and Communities of Interest: Trends in Knowledge Sharing and Assessment (Chapter 4). published by IGI Global, 2010
  10. J. Diesner, E. Ferrari, G. Xu, Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, Sydney, Australia, July 31 – August 03, 2017. ACM 2017, ISBN 978-1-4503-4993-2
  11. Y. Demazeau, J. Gao, G. Xu, J. Kozlak, K. Müller, I. Razzak, H. Chen, Y. Gu, Proceedings of 2017 International Conference on Behavioral, Economic, Socio-cultural Computing, BESC 2017, Krakow, Poland, October 16-18, 2017. IEEE 2017, ISBN 978-1-5386-2365-7
  12. G. Li, Y. Demazeau, G. Xu, P. Wang, L. S. L. Wang, G. Liu, Proceedings of 2016 International Conference on Behavioral, Economic and Socio-cultural Computing, BESC 2016, Durham, NC, USA, November 11-13, 2016. IEEE 2016, ISBN 978-1-5090-6164-8
  13. G. Xu, Y. Demazeau, S. Chen, J.e Wu, M. Gavin, I. King, J. Cao, Z. Wu, Z. Bu, Proceedings of 2015 International Conference on Behavioral, Economic and Socio-cultural Computing, BESC 2015, Nanjing, China, October 30 – December 1, 2015. IEEE 2015, ISBN 978-1-4673-8783-5
  14. H. Liu, G. Xu, and W. Nejdl, Proceedings of 2014 International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2014, Shanghai, China, October 30 – November 1, 2014. IEEE 2014, ISBN 978-1-4799-6980-7
  15. L Cao, G. Xu et al, Behavior and Social Computing, LNCS 8178, 2013, Springer
  16. J. Pei, V. Tseng, L. Cao, H. Motoda, G. Xu(Eds.): Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Lecture Notes in Computer Science, 7818 and 7819, Springer 2013, ISBN 978-3-642-37452-4
  17. Q. Sheng, G. Wang, C. S. Jensen, G. Xu, Web Technologies and Applications– 14th Asia-Pacific Web Conference, APWeb 2012, Kunming, China, April 11-13, 2012. Proceedings Springer 2012
  18. J. He, X. Liu, E. Krupinski and G. Xu; Health Information Science– First International Conference, HIS 2012, Beijing, China, April 8-10, 2012. Proceedings, Springer 2012
  19. Y. Zhang, G. Yu, E. Bertino and G. Xu, Progress in WWW Research and Development, APWeb 2008: 10th Asia-Pacific Web Conference, Shenyang, China, April 26 -28, 2008, Proceeding Springer 2008
  20. Y. Ishikawa, J. He, G. Xuet al, Advanced Web & Network Technologies, and Applications, APWEB 2008 workshops, Shenyang, China, April 26 -28, 2008, Proceeding Springer (LNCS 4977) 2008
  21. Y. Zhang, G. Xu, Singular Value Decomposition, Chapter in Encyclopedia of Database Systems, Springer Press, 2009

Papers in Refereed Journals

  1. D Wang, X Zhang, Z Xiang, D Yu, G Xu, S Deng, Sequential Recommendation Based on Multivariate Hawkes Process Embedding With Attention, accepted in IEEE Transactions on Cybernetics 2021
  2. Z Cui, H Chen, L Cui, S Liu, X Liu, G Xu, H Yin, Reinforced KGs reasoning for explainable sequential recommendation, accepted in World Wide Web, 1-24, 2021
  3. Y Han, P Gu, W Gao, G Xu, J Wu, Aspect-level sentiment capsule network for micro-video click-through rate prediction, accepted in World Wide Web, 1-20, 2021
  4. P Wang, L Li, R Wang, G Xu, J Zhang, Socially-driven multi-interaction attentive group representation learning for group recommendation, Pattern Recognition Letters 145, 74-80, 2021
  5. Y ShuQ LiC XuS LiuG Xu*, V-SVR+: Support Vector Regression with Variational Privileged Information, IEEE Transactions on Multimedia, 2021
  6. N Vo, S Liu, X Li, G Xu*: Leveraging unstructured call log data for customer churn prediction. Knowl. Based Syst. 212: 106586 (2021)
  7. Z Li, H Xie, G Xu, Q Li, M Leng, C Zhou: Towards purchase prediction: A transaction-based setting and a graph-based method leveraging price information. Pattern Recognit. 113: 107824 (2021)
  8. X Li, Y Cao, Q Li, Y Shang, Y Li, Y Liu, G Xu: RLINK: Deep reinforcement learning for user identity linkage. World Wide Web 24(1): 85-103 (2021)
  9. P Wang, L Li, R Wang, G Xu, J Zhang: Socially-driven multi-interaction attentive group representation learning for group recommendation. Pattern Recognit. Lett. 145: 74-80 (2021)
  10. J. Yin, Q. Li, S. Liu, Z. Wu, G. Xu*, Leveraging Multi-level Dependency of Relational Sequences for Social Spammer Detection, Neurocomputing, 428: 130-141 (2021)
  11. M. Gu, Y. Gu, W. Luo, G. Xu, Z. Yang, J. Zhou & W. Qu, From text to graph: a general transition based AMR parsing using neural network, Neural Computing & Applications, Oct 2020
  12. P. Gu, Y. Han, W. Gao, G. Xu, J. Wu, Enhancing Session-based Social Recommendation through Item Graph Embedding and Contextual Friendship Modelling, Neurocomputing 419: 190-202 (2021) (IF: 4.072, JCR-Q1)
  13. I. RazzakK. ZafarM. Imran, G. Xu, Randomized nonlinear one-class support vector machines with bounded loss function to detect of outliers for large scale IoT data. Future Generation Computer System 112: 715-723 2020
  14. D Xu, D Wang, G Xu, D Yu, Time-Aware Sequence Model for Next-Item Recommendation, Applied Intelligence  51(2): 906-920 (2021) IF=3.325), June 2020
  15. W. Hua, Y. Sui, Y. Wan, G. Liu, G. Xu, FCCA: Hybrid Code Representation for Functional Clone Detection Using Attention Networks, IEEE Transactions on Reliability, 70(1): 304-318 (2021)
  16. D. Wang, X. Zhang, D. Yu, G. Xu and S Deng, CAME: Content and Context-Aware Music Embedding for Recommendation, IEEE Trans. Neural Network Learning Systems, 32(3): 1375-1388 (2021)
  17. Z. Wu, R. Wang, Q Li, X. Lian, G. Xu, E. Chen, X. Liu, A location privacy-preserving system based on query range cover-up for location-based services, accepted in IEEE Transactions on Vehicular Technology,  69(5): 5244-5254 (2020) (IF: 5.539)
  18. W. Wang, Y. Zhang, Y. Sui, Y Wan, Z. Zhao, J Wu, P Yu, *G. Xu, Reinforcement-Learning-Guided Source Code Summarization via Hierarchical Attention, accepted in IEEE Transactions on Software Engineering, 2020 (IF: 4.778, JCR- Q1)
  19. I. Razzak, R. M. Abu-Saris, M. Blumenstein, *G. Xu, Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection. Neural Networks121: 441-451, 2020 (IF: 5.785, JCR-Q1)
  20. Y. Shu, Q. Li, S. Liu, G. Xu, Learning with Privileged Information for Photo Aesthetic Assessment, accepted in Neurocomputing 404: 304-316 (2020) (IF: 4.072, JCR-Q1)
  21. Y. Wang, C. Zhang, S. Wang, P. S. Yu, L. Bai, L. Cui, Guandong Xu, Generative Temporal Link Prediction via Self-tokenized Sequence Modeling, accepted in World Wide Web Journal, April 2020 (IF: 1.77, CORE-A, CCF-B)
  22. I. Razzak, IA Hameed, *G. Xu, Robust Sparse Representation and Multiclass Support Matrix Machines for the Classification of Motor Imagery EEG Signals, IEEE Journal of Translational Engineering in Health and Medicine 2019
  23. N. Vo, S. Liu, X. He, *G. Xu Deep Learning for Decision Making and the Optimization of Socially Responsible Investments and Portfolio, Decision Support Systems, accepted on 4 July, 2019 (IF: 3.847, JCR-Q1)
  24. I. Razzak, M. Blumenstein, G. Xu*, Multiclass Support Matrix Machines by Maximizing the Inter-class Margin for Single Trial EEG Classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(6) 2019 (IF: 3.978, JCR-Q1)
  25. I. Razzak, M. Imran, G. Xu, Efficient Brain Tumor Segmentation with Multi-scale Two-Pathway-Group Conventional Neural Networks, accepted in Journal of Biomedical and Health Informatics(Oct 2018, IF: 3.85, JCR-Q1)
  26. I. Razzak, M. Imran, and G. Xu, Big Data Analytics for Preventive Medicine, accepted in Neural Computing and Applications(Jan 2019, IF: 4.213, JCR-Q1)
  27. Z. Saeed, R. Ayaz Abbasi, O. Maqbool, A. Sadaf, I. Razzak, A. Daud, N. Radi Aljohani, G. Xu, What’s Happening Around the World? A Survey and Framework on Event Detection Techniques on Twitter, Journal of Grid Computing17(2): 279-312, 2019 (IF: 3.288, JCR-Q1)
  28. Z Saeed, RA Abbasi, I Razzak, O Maqbool, A Sadaf, G Xu, Enhanced Heartbeat Graph for Emerging Event Detection on Twitter using Time Series Networks, accepted in Expert Systems with Applications(June 2019, IF: 4.929, JCR-Q1)
  29. Z. Saeed, R. Abbasi, I. Razzak, G. Xu, Event Detection in Twitter Stream using Weighted Dynamic Heartbeat Graph Approach, in IEEE Computational Intelligence Magazine,14(3): 29-38 2019 (IF: 6.61, JCR-Q1)
  30. Naseer, M. Rani, S. Naz, M. Razzak, M. Imran, G. Xu, Refining Parkinson’s neurological disorder identification through deep transfer learning, accepted in Neural Computing and Applications(Dec 2018, IF: 4.213, JCR-Q1)
  31. X. Cao, B. Qiu, X. Li, Z. Shi, G. Xu, J. Xu, Multidimensional Balance-Based Cluster Boundary Detection for High-Dimensional Data. IEEE Trans. Neural Network Learning Systems30(6): 1867-1880, 2019
  32. H. Zhang, G. Xu, X. Liang, G. Xu, F. Li, K. Fu, L. Wang, T. Huang, An Attention-Based Word-Level Interaction Model for Knowledge Base Relation Detection. IEEE Access6: 75429-75441, 2018
  33. Z. Wu, C. Zheng, Jian Xiejian, Z. Zhou, Guandong Xu, Enhong Chen, An approach for the protection of users’ book browsing preference privacy in a digital library. The Electronic Library, 36(6): 1154-1166, 2018
  34. Y Wan, G Xu*,, L. Chen, Z. Zhao, Ji. Wu, Exploiting Cross-source Knowledge for Warming up Community Question Answering Services, Neurocomputing 320: 25-34, 2018 (IF: 3.241, JCR-Q1)
  35. Z. Wu, G. Xu, and E. Chen, Covering the Sensitive Subjects to Protect Personal Privacy in Personalized Recommendation, IEEE Transactions on Services Computing, 11(3): 493-506, 2018 (IF: 4.418, JCR-Q1)
  36. D Wang, S Deng, G Xu*, Sequence-based context-aware music recommendation, Information Retrieval Journal, 21 (2-3), 230-252, 2018 (IF: 1.488)
  37. Q. Liu, R.Wu, E. Chen, G.Xu, Y. Su, Z. Chen, Fuzzy Cognitive Diagnosis for Modelling Examinee Performance, ACM Transactions on Intelligent Systems and Technology, 9(4): 48:1-48:26, 2018 (IF: 3.19, JCR-Q1)
  38. K Ji, Z Chen, R Sun, K Ma, Z Yuan, G Xu, GIST: A generative model with individual and subgroup-based topics for group recommendation, Expert Systems with Applications,94, 81-93, 2018 (IF: 3.768, Q1)
  39. Z. Wu, G. Xu, C. Lu, E. Chen, F. Jiang, G. Li, An effective approach for the protection of privacy text data in the CloudDB. World Wide Web,21(4): 915-938, 2018
  40. H. Ying, J. Wu, G. Xu*, Y. Liu, T. Liang, X. Zhang, H Xiong, Time-aware metric embedding with asymmetric projection for successive POI recommendation, World Wide Web, 1-16, 22(5), 2209-2224 (2019)
  41. Y. Gu, M. Gu, Y. Long, G. Xu, Z. Yang, J. Zhou, W Qu, An enhanced short text categorization model with deep abundant representation, World Wide Web, 21(6): 1705-1719 (2018)
  42. Y. Wan, L. Chen, G. Xu*, Z. Zhao, J. Tang, J. Wu, SCSMiner: mining social coding sites for software developer recommendation with relevance propagation, World Wide Web, 21(6): 1523-1543 (2018)
  43. X Cao, B Qiu, G Xu, BorderShift: Toward optimal MeanShift vector for cluster boundary detection in high dimensional data, Pattern Analysis and Applications, 22(3): 1015-1027 (2019)
  44. D. Yu, B. Fu, G. Xu,A. Qin, Constrained nonnegative matrix factorization-based semi-supervised multi-label learning, International Journal of Machine Learning and Cybernetics, 10(5): 1093-1100 (2019)
  45. L. Li, J. Liu, Y. Sun, G. Xu, J. Yuan, L. Zhong, Unsupervised Keyword Extraction from Microblog Posts via Hashtags,Journal of Web Engineering 17 (1&2), 093-12, 2018
  46. S. Deng, L. Huang, G. Xu, X. Wu, Z. Wu, On deep learning for trust-aware recommendations in social networks, IEEE Transactions on Neural Networks and Learning Systems,28 (5), 1164-1177, 2017
  47. L. Hu, L. Cao, J. Cao, Z. Gu, G. Xu, J. Wang, Improving the Quality of Recommendations for Users and Items in the Tail of Distribution. ACM Transactions on Information Systems,35(3): 25:1-25:37, 2017
  48. Z. Wu, L. Lei, G. Li, H. Huang, C. Zheng, E. Chen, G. Xu. A topic modeling based approach to novel document automatic summarization. Expert Systems with Applications84: 12-23, 2017
  49. Z. Wu, H. Zhu, G. Li, Z. Cui, H. Huang, J. Li, E. Chen, G. Xu, An efficient Wikipedia semantic matching approach to text document classification.Information Sciences, 393: 15-28, 2017
  50. D. Wang, S Deng, X Zhang, G Xu, Learning to embed music and metadata for context-aware music recommendation, World Wide Web, 21(5): 1399-1423 (2018)
  51. L. Hu, L. Cao, J. Cao, Z. Gu, G. Xu, D. Yang, Learning Informative Priors from Heterogeneous Domains to Improve Recommendation in Cold-Start User Domains. ACM Transactions on Information Systems,35(2): 13:1-13:37, 2016
  52. T. Liang, L. Chen,, J. Wu, G. Xu, Z. Wu, SMS: A Framework for Service Discovery by Incorporating Social Media Information, IEEE Transaction on Service Computing12(3): 384-397 (2019)
  53. Y. Xun, R. Paulet, E. bertino, G. Xu, Private Cell Retrieval from Data Warehouses, IEEE Transactions on Information Forensics & Security, 11(6): 1346-1361 (2016)
  54. G. Xu, B. Fu, and Y. Gu, Point-Of-Interest Recommendations via Supervised Random Walk, IEEE Intelligent Systems, 31(1): 15-23, 2016
  55. Z. Zhang, Y. Liu, G. Xu,and G. Luo, Recommendation using DMF-based fine tuning method, J Intelligent Information Systems, 47(2): 233-246 (2016)
  56. X. Li, G. Xu, E. Chen, Y. Zong, Learning recency based comparative choice towards point-of-interest recommendation. Expert Syst. Appl. 42(9): 4274-4283, 2015
  57. F. Li, G. Xu, L. Cao, Two-level matrix factorization for recommender systems, Neural Computing And Applications(Published online in September 2015)
  58. S. Deng, D Wang, X Li, and G. Xu, Exploring User Emotion in Microblogs for Music Recommendation, Expert Syst. Appl.(accepted in August 2015)
  59. Y. Li, Y. Li, and G. Xu, Protecting Private Geosocial Networks AgainstPractical Hybrid Attacks With Heterogeneous Information, Neurocomputing(accepted in Sep 2015)
  60. Z. Wu J. Shi, C. Lu, E. Chen, G. Xu, G. Li, S. Xie, P. S. Yu, Constructing plausible innocuous pseudo queries to protect user query intention, Information Sciences, Volume 325, 215–226, 2015
  61. G. Xu and Z. Wu, Group Recommendation and Behavior, IEEE Intelligent Systems, 29(4), 2014 (SCI Impact Factor: 1.92)
  62. S. Deng, L. Huang, G. Xu. Socialnetwork-based service recommendation with trust enhancement. Expert Syst. Appl. 41(18): 8075-8084, 2014
  63. G. Xu, Z. Wu, E. Chen, Improving Contextual Semantic Matching by Using Wikipedia Thesaurus Knowledge, Knowledge and Information Systems(accepted), 2014
  64. B. Fu, Z. Wang, G. Xu, L. Cao, Multi-label learning based on iterative label propagation over graph, Pattern Recognition Letters,42: 85-90, 2014 (ERA B)
  65. G. Xu, Y. Zong, P. Jin, R. Pan, Z. Wu,KIPTC: A Kernel Information Propagation Tag Clustering Algorithm, International Journal of Intelligent Information System (accepted), 2013
  66. Z. Wu,G. Xu, C. Lu, E. Chen, Y. Zhang and H. Zhang, Position-wise contextual advertising: Placing relevant ads at appropriate positions of a web page, Neurocomputing (accepted), 2013
  67. Y. Gu, Z. Yang, G. Xu, M. Nakano, M. Kitsuregawa, Exploration on Efficient Similar Sentences Extraction, World Wide Web Journal(ERA A Journal, accepted in Nov 2012, DOI: 10.1007/s11280-012-0195-z)
  68. Durao, K. Bayyapu, G. Xu, P. Dolog and R. Lage, Expanding User’s Query with Tag-Neighbors for Effective Medical Information Retrieval, Multimedia Tools and Applications(DOI: 10.1007/s11042-012-1316-5, available online in December 2012, ERA B Journal)
  69. L. Li, L. Zhong G. Xu and M. Kitsuregawa, A Feature-free Search Query Classification Approach Using Semantic Distance, Expert Systems with Applications An International Journal, Volume 16, Issue 3, pp 273-297, 2013 (ERA A)
  70. L. Li, G. Xu, Z. Yang Y. Zhang and M. Kitsuregawa, An Efficient Approach to Suggesting Topically Related Web Queries Using Hidden Topic Model, World Wide Web Journal, 2012, DOI 10.1007/s11280-011-0151-3, (ERA A)
  71. Z. Wu, G. Xu, P. Dolog and Y. Zhang, An Improved Contextual Advertising Matching Approach based on Wikipedia Knowledge, the Computer Journal, 55(3): 277-292, 2012 (ERA A*)
  72. Z. Wu, G. Xu, Z. Yu, X. Yi, E. Chen, Y. Zhang, Executing SQL Queries over Encrypted Character Strings in the Database-As-Service Model, Knowledge-based Systems, 2012
  73. Z. Wu, G. Xu, Y. Zhang, Z. Cao, C. Lu and Z. Hu, GMQL: A GraphicalMultimedia Query Language, Knowledge-based Systems Journal, 26(2012), Pages135-143, 2012 (ERA B)
  74. Y. Zong, G. Xu, P. Jin, Y. Zhang and E. Chen, HC_AB: A New Heuristic Clustering Algorithm based on Approximate Backbone, Information Processing Letter, Volume 111, Issue 17, Pages 857-863, 2011 (ERA B)
  75. L. Li, G. Xu, Y. Zhang and M. Kitsuregawa, Random Walk based Rank Aggregation to Improving Web Search, Knowledge-based Systems, Volume 24, Issue 7, Pages 943-951, 2011 (ERA B)
  76. G. Xu, L. Li, Y. Zhang, X. Yi and M. Kitsuregawa, Modeling User Hidden Navigational Behavior for Web Recommendation, Web Intelligence and Agent Systems: An International Journal, Vol.9, No.3, 2011
  77. Y. Zong, G. Xu, Y. Zhang, H. Jiang and M. Li, A Robust Iterative Refinement Clustering Algorithm with Smoothing Search Space, Knowledge-Based Systems, 23 (2010) 389–396, 2010 (ERA B)
  78. J. Thongkam, G. Xu, Y. Zhang and F. Huang, Toward Breast Cancer Survivability Prediction Models through Improving Training Space, Expert System with Applications, 36(10): 12200-12209 (2009), 2009 (ERA B)
  79. Y. Zhang and G. Xu*, On Web Communities Mining and Recommendation, Concurrency and Computation: Practice and Experience, p 561-582, Volume 21 Issue 5, 2008 (ERA A)
  80. W. Liu, L. Gao, Q. Zhang, G. Xu, X. Zhu, X. Liu and J. Xu, “A Random Walk DNA Algorithm for the 3-SAT Problem, Current Nanoscience, pp.83-87, No. 1,Volume 1, 2005 (ERA B)

Papers in Refereed Conference Proceedings

  1. S Zhang, H Chen, X Ming, L Cui, H Yin, G Xu, Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems, accepted at KDD21 (Core-A* Conference)
  2. H Zogan, I Razzak, S Jameel, G Xu, DepressionNet: Learning Multi-modalities with User Post Summarization for Depression Detection on Social Media. SIGIR 2021: 133-142 (Core-A* Conference)
  3. Y Wu, J Cao, G Xu, Yudong Tan, TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers, in SIGIR21, 1013-1022 (Core-A* Conference)
  4. Qian Li, Zhichao Wang, Gang Li, Jun Pang, Guandong Xu; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, pp. 3835-3844 (Core-A* Conference)
  5. Y Chu, L Li, Q Xie, G Xu, C2-Guard: A Cross-Correlation Gaining Framework for Urban Air Quality Prediction. PAKDD (1) 2021: 779-790
  6. H Chen, Y. Li, X Sun, G. Xu*. H Yin, Temporal Meta-path Guided Explainable Recommendation, WSDM 2021 1056-1064 (Core-A* Conference)
  7. Y. Wu, J. Cao, G. Xu, FAST: A Fairness Assured Service Recommendation StrategyConsidering Service Capacity Constraints, accepted in ICSOC 2020 (CORE-A Conference)
  8. Y. Shu, Y, Sui, H. Zhang, G. Xu, Perf-AL: Performance Prediction for Configurable Software through Adversarial Learning, accepted in the 2020 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2020), June 2020 (CORE-A conference, acceptance rate 21%)
  9. Biddle, S. Liu, A. Joshi, C. Paris, G. Xu, Leveraging Sentiment Distributions to Distinguish Figurative from Literal Health Reports on Twitter, accepted as regular paper in 2020 International World Wide Web Conference (Core-A* Conference)
  10. Wan, J. Shu, Y. Sui, G. Xu, Z. Zhao, J. Wu, S. Yu, Multi-modal Attention Network Learning for Semantic Source Code Retrieval. ASE 2019: 13-25
  11. Zheng, Y. Cai, J. Xu, H Leung, G. Xu, A Boundary-aware Neural Model for Nested Named Entity Recognition. EMNLP/IJCNLP2019: 357-366
  12. Shu, G. Xu, Emotion Recognition from Music Enhanced by Domain Knowledge. PRICAI(1) 2019: 121-134
  13. Wang, Q. Li, G. Li, G. Xu, Polynomial Representation for Persistence Diagram, CVPR 2019: 6123-6132 (Core-A* Conference)
  14. Zhou, S. Liu, G.Xu*, W Zhang, On Completing Sparse Knowledge Graph with Transitive Relation Embedding, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), January 27 – February 1, Honolulu, Hawaii, USA
  15. Y Wan, Z Zhao, M Yang, G Xu, H Ying, J Wu, P S. Yu, Improving Automatic Source Code Summarization via Deep Reinforcement Learning, appeared in ASE 2018(CORE A)
  16. Ying, F. Zhuang, F. Zhang, Y. Liu, G. Xu, X. Xie, H. Xiong, J. Wu, Sequential Recommender System based on Hierarchical Attention Networks, appeared in IJCAI 2018(CORE A*)
  17. Brownlow, C. Chu, B. Fu, G. Xu, B. Culbert, Q. Meng, Cost-sensitive Churn Prediction in Fund Management Services, in the 23rd International Conference on Database Systems for Advanced Applications (DASFAA 2018), 21-24 May, 2018, Gold Coast, Australia (CORE A)
  18. Vo, S. Liu, G. Xu, Client Churn Prediction with Call Log Analysis, in the 23rd International Conference on Database Systems for Advanced Applications (DASFAA 2018), 21-24 May, 2018, Gold Coast, Australia (CORE A)
  19. Zhou, G. Xu, S. Liu, Knowledge-based Recommendation with Hierarchical Collaborative Embedding, in the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), June 3rd – 6th, 2018, Melbourne, Australia (CORE A)
  20. Vo, S. Liu, G. Xu, Multimodal Mixture Density Boosting Network for Personality Mining, in the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), June 3rd – 6th, 2018, Melbourne, Australia (CORE A)
  21. Saeed, I. Razzak, R. Abbasi, G. Xu, Text Stream to Temporal Network – A Dynamic Heartbeat Graph to Detect Emerging Events on Twitter, in the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), June 3rd – 6th, 2018, Melbourne, Australia (CORE A)
  22. Yin, Z. Zhou, S. Liu, Z. Wu, G. Xu, Social Spammer Detection: A Multi-Relational Embedding Approach, in the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), June 3rd – 6th, 2018, Melbourne, Australia (CORE A)
  23. Razzak, R. A. Saris, G. Xu, Robust 2D Joint Sparse Principle Component Analysis with F-norm Minimization for Sparse Modelling: 2D-RJSPCA, in the 2018 International Joint Conference on Neural Networks (IJCNN 2018), 8-13 July 2018, Rio De Janeiro, Brazil (CORE A)
  24. Brownlow, C. Chu, G. Xu, B. Culbert, B. Fu and Q. Meng, A Multiple Source based Transfer Learning Framework for Marketing Campaigns, in the 2018 International Joint Conference on Neural Networks (IJCNN 2018), 8-13 July 2018, Rio De Janeiro, Brasil (CORE A)
  25. Biddle, S. Liu, P. Tilocca, G. Xu, Automated Underwriting in Life Insurance: Predictions and Optimisation, Australasian Database Conference (ADC 2018), 135-146, 2018
  26. Culbert, B. Fu, J. Brownlow, C. Chu, Q. Meng, G. Xu, Customer Churn Prediction in Superannuation: A Sequential Pattern Mining Approach, Australasian Database Conference (ADC 2018), 123-134, 2018 (Best Student Paper Award)
  27. M Gui, Z Zhang, Z Yang, Y Gu, G Xu, An Effective Joint Framework for Document Summarization, Companion of the The Web Conference 2018 on The Web Conference 2018 (WWW 2018), 121-122
  28. Liu, N. Pang, G. Xu, H. Liu, Collaborative Filtering via Different Preference Structures. KSEM 2017: 309-321
  29. Hu, L. Cao, S. Wang, G. Xu, J. Cao, Z. Gu, Diversifying Personalized Recommendation with User-session Context. IJCAI 2017: 1858-1864
  30. Wu,G. Xu, E. Chen, Q. Liu, W. Ng, Knowledge or Gaming? Cognitive Modelling Based on Multiple-Attempt Response, in 26th International World Wide Web Conference (WWW 2017), 2-7 April, 2017, Perth Australia.
  31. Wang, G. Xuand S. Deng, Music Recommendation via Heterogeneous Information Graph Embedding, in the 2017 International Joint Conference (IJCNN 2017), Anchorage, Alaska, USA, May 14–19, 2017.
  32. Zhou, G. Xu, W. Zhu, J. Li, W. Zhang, Structure Embedding for Knowledge Base Completion and Analytics, in the 2017 International Joint Conference (IJCNN 2017), Anchorage, Alaska, USA, May 14–19, 2017.
  33. Guo, Y. Bin, Z. Yang, G. Xu,An Enhanced Convolutional Neural Network Model for Answer Selection, in 26th International World Wide Web Conference (WWW 2017), 2-7 April, 2017, Perth Australia
  34. Y Sun, L Li, Z Xie, Q Xie, X Li, Xu, Co-training an Improved Recurrent Neural Network with Probability Statistic Models for Named Entity Recognition, in the 22nd International Conference on Database Systems for Advanced Applications (DASFAA 2017), March 27-30, 2017, Suzhou, China
  35. Han, Y. Wan, L. Chen, G.Xu, Jian Wu, Exploiting Geographical Location for Team Formation in Social Coding Sites, in the 2017 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017), 23-26 May, 2017, Jeju, South Korea
  36. Wang, S. Deng, S. Liu,G. Xu, Improving Music Recommendation Using Distributed Representation. WWW (Companion Volume) 2016: 125-126
  37. Chen, X. Li, L. Li,G. Liu, G. Xu, ModelingUser Mobility via User Psychological and Geographical Behaviors Towards Pointof-Interest Recommendation. DASFAA (1) 2016: 364-380 (ERA A)
  38. Li, G Xu, E. Chen, and L. Xin, Learning User Preferences across Multiple Aspects for Merchant Recommendation, in the Proceedings of the 2015 International Conference on Data Mining (ICDM 2015), 14-17 Nov, 2015, Atlantic City, USA
  39. Li, *G. Xu, L. Cao, CoupledMatrix Factorization within Non-IID Context, in the Proceedings of the 19th Pacific-Asia Conference On Knowledge Discovery and Data Mining (PAKDD 2015), 19-22 May, 2015, Ho Chi Minh City, Vietnam (Regular Paper, Acceptance Rate 6.6%)
  40. Fu, *G. Xu, L. Cao, Coupling Multiple Views of Relations for Recommendation, in the Proceedings of The 19th Pacific-Asia Conference On knowledge Discovery and Data Mining (PAKDD 2015), 19-22 May, 2015, Ho Chi Minh City, Vietnam (Regular Paper, Acceptance Rate 6.6%)
  41. Li, *G. Xu, E. Chen, and L. Li, 2015, Mars: A Multi-Aspect Recommender System for Point-Of-Interest, in the Proceeding of 2015 International Conference of Data Engineering (ICDE 2015), 13-17 April, 2015, Seoul, Korea
  42. Hu, J. Cao, G. Xu, L. Cao, Z. Gu and W. Cao, Deep Modeling of Group Preferences for Group-basedRecommendation, in the Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), July 27–31, 2014 in Québec City, Québec, Canada
  43. Li, L. Zhang, P. Luo, E. Chen, G. Xu, Y. Zong and C. Guan, Mining User Tasks from Print Logs, in the Proceedings of 2014 International Joint Conference on Neural Networks (IJCNN 2014), July 06-11, 2014, Beijing, China (ERA A)
  44. Fu, G. Xu, Z. Wang, L. Cao, Leveraging Supervised Label Dependency Propagation for Multi-label Learning, in the Proceedings of the 2013 IEEE International Conference on Data Mining (ICDM 2013), Dallas, Texas / December 7-10, 2013
  45. Li, G. Xu, L. Cao, and X. Fan, CGMF: Coupled Group-based Matrix Factorization for Recommender System, in the Proceedings of the 14th International Conference on Web Information System Engineering (WISE 2013), October 13-15, 2013, Nanjing, China (ERA A)
  46. Wu, W. Yin, J. Cao, G. Xu, and A. Cuzzocrea, Community Detection in Multi-relational Social Networks, in the Proceedings of the 14th International Conference on Web Information System Engineering (WISE 2013), October 13-15, 2013, Nanjing, China (ERA A)
  47. Hu, J. Cao, G. Xu, et al.,Cross-Domain Collaborative Filtering viaBilinear Multilevel Analysis, in the Proceedings of 23rd International Joint Conference of Artificial Intelligence (IJCAI 2013), August 3-9, 2013, Beijing, China (ERA A)
  48. Hu, J. Cao, G. Xu, L. Cao, Personalized Recommendation via Cross-DomainTriadic Factorization,in the Proceedings of 22nd International World Wide Web Conference (WWW 2013). May 13-17, 2013, Rio de Janeiro, Brazil (ERA A)
  49. Wu, A. Chin, G. Xu, L. Du, X. Wang, K. Meng,Y. Guo, Y. Zhou, Who Will Follow Your Shop? Exploiting Multiple Information Sources in Finding Followers, in The 18th International Conference on Database Systems for Advanced Applications (DASFAA 2013), April 22-25, 2013, Wuhan, China (ERA A)
  50. Li, L. Zhang, E. Chen, Y. Zong, G. Xu, Mining Frequent Patterns in Print Logs with Semantically Alternative Labels, in the Proceedings of 9th International Conference on Advanced Data Mining and Applications (ADMA’2013), December 14-16, 2013 (ERA B)
  51. Yi, R. Paulet, E. Bertino, G. Xu, Private data warehouse queries. SACMAT 2013: 25-36
  52. You, G. Xu, J. Cao, Y. Zhang, G. Huang, Leveraging Visual Features and Hierarchical Dependencies for Conference Information Extraction. APWeb 2013: 404-416
  53. Liu, D. Fan, M. Liu, G. Xu, S. Chen, MapReduce-BasedParallel Clustering Algorithm for Large Protein-Protein Interaction Networks, in the Proceedings of 8th International Conference on Advanced Data Mining and Applications (ADMA 2012), Dec 15-18, Nanjing, china (ERA B)
  54. Zong, G. Xu, P. Jin. X. Yi and E. Chen, A projective clustering algorithm based on significant local dense areas, in the Proceedings of 2012 IEEE International Joint Conference on Neural Networks (IJCNN 2012), June 10-15, 2012, Brisbane, Australia (ERA A)
  55. Chen, L. Li, H. Xiao, G. Xu, Recommending Related Microblogs: A Comparison Between Topic and WordNet based Approaches, in the Proceedings of Twenty-sixth AAAI Conference on Artificial Intelligence (AAAI-12), July 24 – 28, 2012, Toronto, Ontario, Canada (ERA A)
  56. Fu, Z.-H. Wang, R. Pan, G. Xu, and P. Dolog, Learning Tree Structure of Labels Dependency for Multi-label Learning, in the Proceedings of 16 Pacific-Asia Knowledge Discovery and Data Mining (PAKDD 2012), May 29 – June 1, 2012, Kuala Lumpur (ERA A)
  57. Hu, J. Cao1, G. Xu, and Z. Gu, Latent Informative Links Detection, in the Proceedings of 16th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES 2012), M. Graña et al. (Eds.), IOS Press, 1233 – 1242, San Sebastian, Spain, 10-12 September 2012 (ERA B)
  58. Xu, Y. Gu, P. Dolog, Y. Zhang and M. Kitsuregawa, SemRec: A Semantic Enhancement Framework for Tag based Recommendation, in the Proceedings of Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI-11), August 7 – 11, 2011, in San Francisco, California, USA (ERA A)
  59. Xu, Y. Gu, Y. Zhang and M. Kitsuregawa, TOAST: A Topic-Oriented Tag-based Recommender System, in the Proceedings of The 12th International Conference on Web Information System Engineering (WISE 2011), October 13 – 14, 2011, Sydney, Australia (ERA A)
  60. Wu, G. Xu, Y. Zhang, C. Lu, Z. Hu and J. Lu, Wikipedia-based Contextual Advertising, in the Proceedings of 20th ACM Conference on Information and Knowledge Management (CIKM 2011), October 24-28, 2011, Glasgow, UK (ERA A)
  61. Xu, Y. Zong, R. Pan, P. Dolog and P. Jin, On Kernel Information Propagation for Tag Clustering in Social Annotation Systems, in the Proceedings of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES 2011), IS “Advanced Knowledge-based Systems“, 12-14 September 2011, Kaiserslautern, Germany (ERA B)
  62. Zong, G. Xu, Y. Zhang, E. Chen and P. Jin, APPECT: An Approximate Backbone-based Clustering Algorithm for Tags, in the Proceeding of 7th International Conference on Advanced Data Mining and Applications (ADMA 2011), Dec 17-19, Beijing, China (ERA B)
  63. Zong, G. Xu, P. Dolog and Y. Zhang, Co-Clustering for Weblogs in Semantic Space, in the Proceedings of 11th international Conference on Web Information Systems Engineering (WISE’10), Dec 12-14, 2010, Hong Kong, China (ERA A)
  64. Xu, Y. Zong, P. Dolog and Y. Zhang, Co-Clustering of Web Log using Bipartite Spectral Clustering, in the Proceedings of 14th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 8-10 September 2010 Cardiff, Wales, UK (ERA B)
  65. Lin Li, Xu, Y. Zhang and M. Kitsuregawa, Enhancing Web Search by Aggregating Results of Related Web Queries, in the Proceedings of 10th international Conference on Web Information Systems Engineering (WISE’09), Oct 5-9, 2009, Poznan, Poland (ERA A)
  66. Zhang and G. Xu, Using Web Clustering for Web Community Mining & Analysis, in Proceedings of 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Dec 9-12, 2008, Sydney, Australia.
  67. Thongkam, G. Xu and Y. Zhang, “Adaboost Algorithm with Random Forests for Predicting Breast Cancer Survivability“, in the proceeding of the 2008 International Joint Conference on Neural Networks (IJCNN2008), June 2-6, 2008, Hong Kong (ERA A)
  68. Zhang and G. Xu, “On Web Communities Mining and Analysis“, in Proceeding of the 3rd International Conference on Semantic, Knowledge and Grid (SKG2007), Oct 29-31, Xi’an, China, 2007
  69. Xu, Y. Zhang and R. Begg, “Mining gait pattern for clinical locomotion diagnosis based on clustering technique”, in Proceeding of Second International Conference of Advanced Data mining and Applications (ADMA’2006), Xi’An, Springer LNAI 4093, 2006 (ERA B)
  70. Xu, Y. Zhang and X. Zhou, “ Discovering Task-Oriented Usage Pattern for Web Recommendation” in Proceeding of The 17th Australasian Database Conference (ADC’2006), January 16 – 19, 2006, Tasmania, Australia (ERA B 2010)
  71. Xu, Y. Zhang, J. Ma and X. Zhou, “Discovering User Access Pattern Based on Probabilistic Latent Factor Model“, in Proceedings of 16th Australasian Database Conference (ADC 2005), pp 27-36, 31 January – 3 February 2005, Newcastle, Australia (ERA B)
  72. Xu, Y. Zhang and X. Zhou, “A Latent Usage Approach for Clustering Web Transaction and Building User Profile“, in Proceeding of The First International Conference on Advanced Data Mining and Applications (ADMA’2005) Invited Paper, LNAI 3584, pp 31-42, July 22-24,2005, Wuhan, china (ERA B)
  73. Xu, Y. Zhang and X. Zhou, “A Web Recommendation Technique Based on Probabilistic Latent Semantic Analysis“, in Proceeding of 6th International ference of Web Information System Engineering (WISE’2005), LNCS 3806, pp 15-28, November 22-25, 2005, New York City, USA (ERA A)
  74. Xu, Y. Zhang and X. Zhou, “Towards User Profiling for Web Recommendation“, in Proceeding of The 18th Australian Joint Conference on Artificial Intelligence (AI’2005), LNAI 3809, pp 405-414, December 5-9, 2005, Sydney, Australia (ERA B)
  75. Xu, Y. Zhang and X. Zhou, “Using Probabilistic Semantic Latent Analysis for Web Page Grouping“, in Proceeding of 15th International Workshop on Research Issues on Data Engineering: Stream Data Mining and Applications (RIDE-SDMA’2005), pp 29-36, in conjunction with ICDE’2005, April 3-4, 2005, Tokyo, Japan (ERA B)