Professor Xue Li

Professor

School of Information Technology and Electrical Engineering
Faculty of Engineering, Architecture and Information Technology
xueli@itee.uq.edu.au
+61 7 336 52097

Overview

Qualifications

  • Bachelor of Sciences, Chongqing
  • Master of Sciences, The University of Queensland
  • PhD, Queensland University of Technology

Publications

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Supervision

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Available Projects

  • Description:

    Traditional database queries are used to search for facts from structured database such as RDB (Relational Databases) to satisfy user search conditions. With big data currently available in many ways such as structured and unstructured multi-modalities, user queries should be constructed not only for searching facts, but also for searching patterns, emerging events, and outliers from available big data. This PhD research is to propose a new type of query language that can query on analytic results , to satisfy user requirements for informed decision support. In order to make such a language to be implementable on general big dataset, this PhD research will also define and design a framework that can answer declarative analytic queries by a data-driven approach to apply transparent machine learning algorithms in order to discover unexpected patterns, emerging trends, various correlations from big data. The challenges of this research will be on how to use an end-to-end black-box mechanism to provide big data analytic services to make big data available for general queries beyond classical data warehousing technologies.

    Background:

    In classical DSS systems based on data warehouses and OLAP operations, the queries such as Canned and Continuous Queries would not involve procedural operations that can reflect the dynamic parameters of queries. The operators such as Role-Up, Drill-Down, Slice/Dice, Cube, Pivoting etc, cannot reflect the context of the query objects in their business context. This PhD research will try to introduce more flexible analytical data manipulation operations based on machine learning algorithms that can provide end-to-end queries for strategic DSS with baselines.

  • Description:

    Artificial Intelligence (AI) applications are mostly based on the first-order thinking that is resoning based on deduction, abduction, induction, or eduction. In this way, AI is limited and unable to discover the First Principles such as those in sciences and complex Math Equitions, Laws in Physics and Chemistry. However, this should not prevent AI to be used together with the First Principles in those descovery projects. This PhD research is to design an architecture of AI Application platform that can use First Princile in AI to speed up the human trial-and-error process of experiments, to use First Principle in a more intelligent way to converge an optimazation process which has a large number of iterations faster and scalable for human's research problems.

  • Description:

    Predictive data analytics usually involves Big Data that is distributed in different locations and owned by different organizations, such as the Taxation Office Data, Boarder-Control Customs Data, Crime-Stop Police Data, and Social Security Data. The organizations are legally responsible for the privacy preservation of their data which is of highly risk and sensitive. However, this should not prevent the sharing of those de-identified, privacy preserved data sets for the predictions of pending social-economic events, emerging trends, patterns of relationships, or correlations among entities. Currently, there are many algorithms that can preserve privacy for computing data from multiple owners, such as SMC (secure multi-party computation), Differential Privacy algorithms. However, the predictive tasks often require to use all original raw data for the learning. This would involve the individual organizations to conduct local learning tasks and contribute to global learning with their local models, instead of their sensitive data. Federated learning therefore coming to being as a promising and useful approach to learn from individual datasets and producing a general model for the required predicting tasks. This project is to research on the Federated Learning algorithms that can deal with large distributed, sensitive datasets and derive a computational model to predict some pre-defined tasks. The challenges of this project would be the following three issues in one solution, i.e., data shareability, data privacy, and computational utility.

    Key Terms: Federated Learning, Deep Learning, Distributed Database Technology, Privacy Preservation, Mathematical Modelling, Data Shareability, Computational Utility

View all Available Projects

Publications

Book

Book Chapter

  • Subpaiboonkit, Sitthichoke, Li, Xue, Zhao, Xin, Scells, Harrisen and Zuccon, Guido (2019). Causality discovery with domain knowledge for drug-drug interactions discovery. Advanced data mining and applications. (pp. 632-647) Cham, Switzerland: Springer. doi: 10.1007/978-3-030-35231-8_46

  • Li, Xingjuan, Burnham, Samantha, Fripp, Jurgen, Li, Yu, Li, Xue, Fazlollahi, Amir and Bourgeat, Pierrick (2019). Identification of functional connectivity features in depression subtypes using a data-driven approach. Graph learning in medical imaging. (pp. 96-103) Cham, Switzerland: Springer. doi: 10.1007/978-3-030-35817-4_12

  • Maskari, Sanad Al and Li, Xue (2018). E-nose pattern recognition and drift compensation methods. Electronic nose technologies and advances in machine olfaction. (pp. 38-57) edited by Yousif Albastaki and Fatema Albalooshi. Hershey, PA, United States: IGI Global. doi: 10.4018/978-1-5225-3862-2.ch003

  • Yao, Lina, Sheng, Quan Z., Ngu, Anne H.H., Li, Xue, Benatallah, Boualem and Wang, Xianzhi (2017). Building Entity Graphs for the Web of Things Management. Managing the Web of Things: Linking the Real World to the Web. (pp. 275-303) Cambridge, MA, United States: Elsevier . doi: 10.1016/B978-0-12-809764-9.00013-5

  • Nahar, Vinita, Li, Xue and Pang, Chaoyi (2014). Cyberbullying validation. Handbook on bullying: prevalence, psychological impacts and intervention strategies. (pp. 233-257) edited by Phoebe Triggs. New York, NY, United States: Nova Science Publishers.

  • Mo, John P. T. and Li, Xue (2010). Event management of RFID data streams: Fast moving consumer goods supply chains. Unique radio innovation for the 21st Century: Building scalable and global RFID networks. (pp. 89-109) edited by Damith C. Ranasinghe, Quan Z. Sheng and Sherali Zeadally. Berlin, Heidelberg: Springer-Verlag. doi: 10.1007/978-3-642-03462-6

  • Li, Xue (2009). Database clustering methods. Encyclopedia of Database Systems. (pp. 699-700) United States: Springer.

  • Ding-Yi Chen, Xue Li, Zhao Yang Dong and Xia Chen (2009). Incremental learning for interactive e-mail filtering. Agent technologies and web engineering: Applications and systems. (pp. 134-152) edited by David Rine and Ghazi Alkhatib. Hershey, PA, U.S.A.: IGI Global. doi: 10.4018/978-1-60566-618-1.ch008

  • Li, Xue (2009). K-Means and K-Medoids. Encyclopedia of Database Systems. (pp. 1588-1589) edited by Ling Liu and M. Tamer Özsu. United States: Springer.

  • Li, X. (2003). Intelligent Business Portals. Architectural Issues of Web-Enabled Electronic Business. (pp. 40-51) edited by N. Shi and V. Murthy. London: Idea Group Publishing.

Journal Article

Conference Publication

  • Zhang, Yanjun, Bai, Guangdong, Li, Xue, Curtis, Caitlin, Chen, Chen and Ko, Ryan K. L. (2020). PrivColl: practical privacy-preserving collaborative machine learning. European Symposium on Research in Computer Security, Guildford, United Kingdom, 14-18 September 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-58951-6_20

  • Chen, Tong, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Peng, Wen-Chih, Li, Xue and Zhou, Xiaofang (2020). Sequence-aware factorization machines for temporal predictive analytics. 2020 IEEE 36th International Conference on Data Engineering, Dallas, Texas, United States, 20-24 April 2020. LOS ALAMITOS: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00125

  • Ma, Jingwei, Wen, Jiahui, Zhong, Mingyang, Liu, Liangchen, Li, Chaojie, Chen, Weitong, Yang, Yin, Tu, Hongkui and Li, Xue (2019). DBRec: dual-bridging recommendation via discovering latent groups. CIKM '19, Beijing, China, 3-7 November 2019. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3357384.3357892

  • Utomo, Chandra Prasetyo, Kurniawati, Hanna, Li, Xue and Pokharel, Suresh (2019). Personalised medicine in critical care using Bayesian reinforcement learning. ADMA 2019: Advanced Data Mining and Applications, Dalian, China, 21–23 November, 2019. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-35231-8_47

  • Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Yan, Rui, Nguyen, Quoc Viet Hung and Li, Xue (2019). AIR: Attentional intention-aware recommender systems. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8-11 April 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00035

  • Zhang, Yanjun, Zhao, Xin, Li, Xue, Zhong, Mingyang, Curtis, Caitlin and Chen, Chen (2019). Enabling privacy-preserving sharing of genomic data for GWASs in decentralized networks. Twelfth ACM International Conference on Web Search and Data Mining, Melbourne, VIC, Australia, 11-15 February 2019. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3289600.3290983

  • Chen, Hongxu, Yin, Hongzhi, Chen, Tong, Nguyen, Quoc Viet Hung, Peng, Wen-Chih and Li, Xue (2019). Exploiting centrality information with graph convolutions for network representation learning. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8-11 April 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00059

  • Ji, Shaoxiong, Pan, Shirui, Long, Guodong, Li, Xue, Jiang, Jing and Huang, Zi (2019). Learning private neural language modeling with attentive aggregation. 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 14-19 July 2019. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/IJCNN.2019.8852464

  • Ma, Jingwei, Zhong, Mingyang, Wen, Jiahui, Chen, Weitong, Zhou, Xiaofang and Li, Xue (2019). RecKGC: Integrating Recommendation with Knowledge Graph Completion. 15th International Conference, ADMA 2019, Dalian, China, 21–23 November 2019. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-35231-8_18

  • Zhong, Jiang, Zhang, Pan and Li, Xue (2018). A combined feature approach for speaker segmentation using convolution neural network. 18th Pacific-Rim Conference on Multimedia, PCM 2017, Harbin, China, 28-29 September 2017. Cham, Switzerland: Springer Verlag. doi: 10.1007/978-3-319-77383-4_54

  • Ibrahim, Ibrahim A., Li, Xue, Zhao, Xin, Maskari, Sanad Al, Albarrak, Abdullah M. and Zhang, Yanjun (2018). Automated explanations of user-expected trends for aggregate queries. Pacific-Asia Conference, PAKDD, Melbourne, VIC, Australia, 3-6 June 2018. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-319-93034-3_48

  • Chen, Tong, Li, Xue, Yin, Hongzhi and Zhang, Jun (2018). Call attention to rumors: deep attention based recurrent neural networks for early rumor detection. 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, VIC, Australia, 3 June 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_4

  • Chen, Weitong, Wang, Sen, Long, Guodong, Yao, Lina, Sheng, Quan Z. and Li, Xue (2018). Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit. 18th IEEE International Conference on Data Mining, ICDM 2018, Singapore, 17 - 20 November 2018. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2018.00111

  • Chen, Weitong, Wang, Sen, Zhang, Xiang, Yao, Lina, Yue, Lin, Qian, Buyue and Li, Xue (2018). EEG-based motion intention recognition via multi-task RNNs. 2018 SIAM International Conference on Data Mining, SDM 2018, San Diego, CA, United States, 3-5 May 2018. Society for Industrial and Applied Mathematics Publications. doi: 10.1137/1.9781611975321.32

  • Al-Maskari, Sanad, Ibrahim, Ibrahim A., Li, Xue, Abusham, Eimad and Almars, Abdulqader (2018). Feature extraction for smart sensing using multi-perspectives transformation. Australasian Database Conference, Gold Coast, QLD, Australia, 24-27 May 2018. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-319-92013-9_19

  • Ibrahim, Ibrahim A., Almars, Abdulqader M., Pokharel, Suresh, Zhao, Xin and Li, Xue (2018). Interesting recommendations based on hierarchical visualizations of medical data. 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, VIC, June 3 2018. Springer Verlag. doi: 10.1007/978-3-030-04503-6_6

  • Almars, Abdulqader, Li, Xue, Ibrahim, Ibrahim A. and Zhao, Xin (2018). Learning Concept Hierarchy from Short Texts Using Context Coherence. 19th International Conference on Web Information Systems Engineering, WISE 2018, Dubai, United Arab Emirates, 12 - 15 November 2018. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-02922-7_22

  • Chen, Hongxu, Wang, Hao, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Wang, Weiqing and Li, Xue (2018). PME: projected metric embedding on heterogeneous networks for link prediction. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018, London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3219986

  • Chen, Tong, Chen, Hongxu and Li, Xue (2018). Rumor detection via recurrent neural networks: a case study on adaptivity with varied data compositions. 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, VIC, Australia, 3 June 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_10

  • Pokharel, Suresh, Li, Xue, Zhao, Zin, Adhikari, Anoj and Li, Yu (2018). Similarity computing on electronic health records. Pacific Asia Conference on Information Systems, Yokohama, Japan, 26 - 30 June 2018. Pacific Asia Conference on Information Systems.

  • Li, Qi, Zhong, Jiang, Zheng, Linjiang and Li, Xue (2018). Streaming graph partitioning for large graphs with limited memory. 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017, Guangzhou, China, 12-15 December 2017. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ISPA/IUCC.2017.00193

  • Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Wu, Lin, Wang, Hao, Zhou, Xiaofang and Li, Xue (2018). TADA: trend alignment with dual-attention multi-task recurrent neural networks for sales prediction. 18th IEEE International Conference on Data Mining, ICDM 2018, Singapore, 17-20 November 2018. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ICDM.2018.00020

  • Utomo, Chandra Prasetyo, Li, Xue and Chen, Weitong (2018). Treatment recommendation in critical care: a scalable and interpretable approach in partially observable health states. 39th International Conference on Information Systems, ICIS 2018, San Francisco, California, 13-16 December 2018. Red Hook, NY, United States: Curran Associates.

  • Wan, Shuo, Li, Bohan, Zhang, Anman, Wang, Kai and Li, Xue (2018). Vertical and sequential sentiment analysis of micro-blog topic. 14th International Conference on Advanced Data Mining and Applications, ADMA 2018, Nanjing, China, 16-18 November 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-05090-0_30

  • Li, Xue, Zhao, Xin and Zhong, Mingyang (2017). Advancing public health genomics. 2016 International Workshop on Big Data and Information Security, IWBIS 2016, Jakarta, Indonesia, 18 - 19 October 2016. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IWBIS.2016.7872883

  • Wu, Lin, Haynes, Michele, Smith, Andrew, Chen, Tong and Li, Xue (2017). Generating life course trajectory sequences with recurrent neural networks and application to early detection of social disadvantage. Advanced Data Mining and Applications 13th International Conference, Singapore, November 5–6, 2017. Heidelberg, Germany: Springer . doi: 10.1007/978-3-319-69179-4_16

  • Zheng, Wei, Li, Bohan, Wang, Yanan, Yin, Hongzhi, Li, Xue, Guan, Donghai and Qin, Xiaolin (2017). Group recommender model based on preference interaction. 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, Singapore, Singapore, 5–6 November 2017. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-69179-4_10

  • Wang, Meng, Zhang, Jiaheng, Liu, Jun, Hu, Wei, Wang, Sen, Li, Xue and Liu, Wenqiang (2017). PDD graph: bridging electronic medical records and biomedical knowledge graphs via entity linking. The Semantic Web – ISWC 2017: 16th International Semantic Web Conference Vienna, Austria, October 21–25, 2017 Proceedings, Part II, Vienna, Austria, 21-25 October 2017. Cham, Switzerland: Springer Nature. doi: 10.1007/978-3-319-68204-4_23

  • Haryanto, Toto, Suhartanto, Hem and Lie, Xue (2017). Past, present, and future trend of GPU computing in deep learning on medical images. 9th International Conference on Advanced Computer Science and Information Systems (ICACSIS), Jakarta, Indonesia, 28-29 October 2017. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICACSIS.2017.8355007

  • Chen, Hongxu, Yin, Hongzhi, Li, Xue, Wang, Meng, Chen, Weitong and Chen, Tong (2017). People opinion topic model: opinion based user clustering in social networks. International Conference on World Wide Web Companion, Perth, Australia, 3-7 April 2017. Geneva, Switzerland: International World Wide Web Conferences Steering Committee. doi: 10.1145/3041021.3051159

  • Li, Xingjuan, Li, Yu and Li, Xue (2017). Predicting clinical outcomes of Alzheimer’s disease from complex brain networks. 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, Singapore,, November 5, 2017-November 6, 2017. CHAM: Springer Verlag. doi: 10.1007/978-3-319-69179-4_36

  • Ruan, Wenjie, Xu, Peipei, Sheng, Quan Z., Falkner, Nickolas J. G., Li, Xue and Zhang, Wei Emma (2017). Recovering Missing Values from Corrupted Spatio-Temporal Sensory Data via Robust Low-Rank Tensor Completion. 22nd International Conference on Database Systems for Advanced Applications (DASFAA), Suzhou Peoples R China, Mar 27-30, 2017. CHAM: SPRINGER INTERNATIONAL PUBLISHING AG. doi: 10.1007/978-3-319-55753-3_38

  • Almars, Abdulqader, Li, Xue, Zhao, Xin, Ibrahim, Ibrahim A., Yuan, Weiwei and Li, Bohan (2017). Structured sentiment analysis. 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, Singapore, Singapore, 5–6 November 2017. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-69179-4_49

  • Wang, Sen, Nie, Feiping, Chang, Xiaojun, Li, Xue, Sheng, Quan Z. and Yao, Lina (2017). Uncovering locally discriminative structure for feature analysis. 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016, Riva del Garda, Italy, 19 - 23 September 2016. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-46128-1_18

  • Li, Xue (2016). Opinion search engine. 14th Australasian Data Mining Conference, AusDM 2016, Canberra, ACT, Australia, 6 - 8 December 2016. Brisbane, QLD, Australia: Australian Computer Society.

  • Utomo, Chandra, Li, Xue and Wang, Sen (2016). Classification based on compressive multivariate time series. 27th Australasian Database Conference on Databases Theory and Applications, ADC 2016, Sydney Australia, 28-29 September 2016. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-46922-5_16

  • Al-Maskari, Sanad, Belisle, Eve, Li, Xue, Le Digabel, Sebastien, Nawahda, Amin and Zhong, Jiang (2016). Classification with quantification for air quality monitoring. 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016, Auckland, New Zealand, 19 - 22 April 2016. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-31753-3_46

  • Wang, Xianzhi, Sheng, Quan Z., Yao, Lina, Li, Xue, Fang, Xiu Susie, Xu, Xiaofei and Benatallah, Boualem (2016). Empowering truth discovery with multi-truth prediction. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983767

  • Ruan, Wenjie, Sheng, Quan Z., Xu, Peipei, Tran, Nguyen Khoi, Falkner, Nickolas J. G., Li, Xue and Zhang, Wei Emma (2016). Forecasting seasonal time series using weighted gradient RBF network based autoregressive model. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983899

  • Yao, Lina, Sheng, Quan Z., Li, Xue, Wang, Sen, Gu, Tao, Ruan, Wenjie and Zou, Wan (2016). Freedom: online activity recognition via dictionary-based sparse representation of RFID sensing data. 15th IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, United States, 14-17 November 2015. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2015.102

  • Yao, Lina, Nie, Feiping, Sheng, Quan Z., Gu, Tao, Li, Xue and Wang, Sen (2016). Learning from less for better: semi-supervised activity recognition via shared structure discovery. 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, Heidelberg, Germany, 12-16 September 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2971648.2971701

  • Tang, Xin, Huang, Wei, Li, Xue, Li, Shengli and Liu, Yuewen (2016). Outlier detection via minimum spanning tree. Pacific Asia Conference on Information Systems, PACIS, Chiayi, Taiwan, 27 June - 1 July 2016. Pacific Asia Conference on Information Systems.

  • Li, Jinyan, Li, Xue and Wang, Shuliang (2016). Preface. 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, Gold Coast, QLD, Australia, 12 - 15 December 2016. Berlin, Germany: Springer Verlag. doi: 10.1007/978-3-319-49586-6

  • Wang, Xianzhi, Sheng, Quan Z., Yao, Lina, Li, Xue, Fang, Xiu Susie, Xu, Xiaofei and Benatallah, Boualem (2016). Truth discovery via exploiting implications from multi-source data. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983791

  • Yao, Lina, Sheng, Quan Z., Ruan, Wenjie, Li, Xue, Wang, Sen and Yang, Zhi (2016). Unobtrusive posture recognition via online learning of multi-dimensional RFID received signal strength. 2015 IEEE 21st International Conference on Parallel and Distributed Systems, ICPADS 2015, Melbourne, Victoria, Australia, 14- 17 December 2015. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICPADS.2015.23

  • Ruan, Wenjie, Xu, Peipei, Sheng, Quan Z., Tran, Nguyen Khoi, Falkner, Nickolas J. G., Li, Xue and Zhang, Wei Emma (2016). When sensor meets tensor: filling missing sensor values through a tensor approach. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983900

  • Wang, Xianzhi, Sheng, Quan Z., Fang, Xiu Susie, Yao, Lina, Xu, Xiaofei and Li, Xue (2015). An integrated Bayesian approach for effective multi-truth discovery. 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, Australia, 19-23 October 2015. New York, NY United States: The Association for Computing Machinery. doi: 10.1145/2806416.2806443

  • Wang, Xianzhi, Sheng, Quan Z., Fang, Xiu Susie, Li, Xue, Xu, Xiaofei and Yao, Lina (2015). Approximate truth discovery via problem scale reduction. 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, VIC Australia, 19-23 October 2015. New York, NY United States: The Association for Computing Machinery. doi: 10.1145/2806416.2806444

  • Unankard, Sayan, Li, Xue and Long, Guodong (2015). Invariant event tracking on social networks. 20th International Conference on Database Systems for Advanced Applications, DASFAA 2015, Hanoi, Vietnam, 20-23 April 2015. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-18123-3_31

  • Yao, Lina, Sheng, Quan Z., Ruan, Wenjie, Gu, Tao, Li, Xue, Falkner, Nickolas J.G. and Yang, Zhi (2015). RF-care: device-free posture recognition for elderly people using a passive RFID tag array. 12th International Conference on Mobile and Ubiquitous Systems, Coimbra, Portugal, 22-24 July 2015. ICST. doi: 10.4108/icst.mobiquitous.2015.260064

  • Wang, Sen, Nie, Feiping, Chang, Xiaojun, Yao, Lina, Li, Xue and Sheng, Quan Z. (2015). Unsupervised feature analysis with class margin optimization. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Porto, Portugal, 7-11 September 2015. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-23528-8_24

  • Al-Maskari, Sanad, Li, Xue and Liu, Qihe (2014). An effective approach to handling noise and drift in electronic noses. 25th Australasian Database Conference, ADC 2014, Brisbane, QLD Australia, 14 - 16 July2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-08608-8_21

  • Xu, Pei, Liu, Qihe, Ye, Mao, Yang, Yi, Li, Xue and Ding, Jian (2014). Dynamic background learning through deep auto-encoder networks. 2014 ACM Conference on Multimedia, MM 2014, Orlando, FL, United States, 3 - 7 November 2014. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2647868.2654914

  • Yao, Lina, Sheng, Quan Z., Ngu, Anne H. H., Ashman Helen and Li, Xue (2014). Exploring recommendations in Internet of Things. 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014, Gold Coast, QLD Australia, 6-11 July 2014. New York, NY United States: Association for Computing Machinery. doi: 10.1145/2600428.2609458

  • Yao, Lina, Ruan, Wenjie, Sheng, Quan Z., Li, Xue and Falkner, Nicholas J.G. (2014). Exploring tag-free RFID-based passive localization and tracking via learning-based probabilistic approaches. 23rd ACM International Conference on Information and Knowledge Management, CIKM 2014, Shanghai, China, 3-7 November 2014 . New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2661829.2661873

  • Chen, Ling, Li, Xue, Wang, Sen, Hu, Hsiao-Yun, Huang, Nicole, Sheng, Quan Z. and Sharaf, Mohamed (2014). Mining personal health index from annual geriatric medical examinations. 2014 IEEE International Conference on Data Mining, Shenzhen, China, 14-17 December 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDM.2014.32

  • Unankard, Sayan, Li, Xue, Sharaf, Mohamed, Zhong, Jiang and Li, Xueming (2014). Predicting elections from social networks based on sub-event detection and sentiment analysis. 15th International Conference on Web Information Systems Engineering (WISE 2014), Thessaloniki, Greece, 12-14 October 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-11746-1_1

  • Chang, Xiaojun, Shen, Haoquan, Wang, Sen, Liu, Jiajun and Li, Xue (2014). Semi-supervised feature analysis for multimedia annotation by mining label correlation. 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014, Tainan, Taiwan, 13 - 16 May 2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-06605-9_7

  • Nahar, Vinita, Al-Maskari, Sanad, Li, Xue and Pang, Chaoyi (2014). Semi-supervised learning for cyberbullying detection in social networks. 25th Australasian Database Conference, ADC 2014, Brisbane, QLD, 14 - 16 July2014. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-08608-8_14

  • Ruan, Wenjie, Yao, Lina, Sheng, Quan Z., Falkner, Nickolas J.G. and Li, Xue (2014). TagTrack: device-free localization and tracking using passive RFID tags. 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, London, United Kingdom, 2-5 December 2014. ICST. doi: 10.4108/icst.mobiquitous.2014.258004

  • Zhou, Xiaofang, Sadiq, Shazia, Shen, Heng Tao, Li, Xue, Sharaf, Mohamed A.., Huang, Zi, Zheng, Kai, Hunter, Jane, Green, Peter and Indulska, Marta (2013). Data Centric Research at The University of Queensland. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2536669.2536682

  • Gollapalli, Mohammed and Li, Xue (2013). A framework of Ontology Guided Data Linkage for evidence based knowledge extraction and information sharing. 2013 IEEE 29th International Conference on Data Engineering Workshops, ICDEW 2013, Brisbane, QLD, Australia, 8-11 April 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDEW.2013.6547467

  • Yao, Lina, Sheng, Quan Z., Gao, Byron J., Ngu, Anne H. H. and Li, Xue (2013). A model for discovering correlations of ubiquitous things. 13th IEEE International Conference on Data Mining, ICDM 2013, Dallas, TX United States, 7 - 10 December 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/ICDM.2013.87

  • Nahar, Vinita, Li, Xue, Pang, Chaoyi and Zhang, Yang (2013). Cyberbullying Detection based on text-stream classification. 11th Australasian Data Mining Conference - AusDM'13, Canberra, Australia, 13-15 November 2013. Brisbane QLD Australia: Australian Computer Society.

  • Li, Xue, Sheng, Quan Z., Pang, Chaoyi, Zhao, Xin and Wang, Sen (2013). Effective approaches in human action recognition. 2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS), Bali, Indonesia, 28-29 September 2013. Piscataway, NJ, United States: IEEE Computer Society. doi: 10.1109/ICACSIS.2013.6761544

  • Wang, Sen, Xu, Zhongwen, Yang, Yi, Li, Xue, Pang, Chaoyi and Haumptmann, Alexander G. (2013). Fall detection in multi-camera surveillance videos: experimentations and observations. 1st ACM International Workshop on Multimedia Indexing and Information Retrieval for Heathcare (MIIRH 2013), Barcelona, Spain, 22 October 2013. New York, United States: ACM. doi: 10.1145/2505323.2505331

  • Zhao, Peng, Li, Xue and Wang, Ke (2013). Feature extraction from micro-blogs for comparison of products and services. 14th International Conference on Web Information Systems Engineering, WISE 2013, Nanjing, China, 13 -15 October 2013. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-41230-1_7

  • Unankard, Sayan, Li, Xue and Sharaf, Mohamed A. (2013). Location-based emerging event detection in social networks. 15th Asia-Pacific Web Conference (APWeb), 2013, Sydney, Australia, 4-6 April, 2013. Berlin & Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-37401-2_29

  • Chen, L., Li, X. and Han, J. (2013). MedRank: Discovering influential medical treatments from literature by information network analysis. 24th Australasian Database Conference, ADC 2013, Adelaide, Australia, 29 January 2013 - 1 February 2013. Sydney, NSW, Australia: Australian Computer Society.

  • Zhao, Xin, Wang, Sen, Li, Xue and Zhang, Hao Lan (2013). Online action recognition by template matching. 2nd International Conference on Health Information Science, HIS 2013, London, United Kingdom, 25-27 March 2013. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-37899-7_25

  • Zhao, Xin, Li, Xue, Pang, Chaoyi, Zhu, Xiaofeng and Sheng, Quan Z. (2013). Online human gesture recognition from motion data streams. 21st ACM International Conference on Multimedia, MM 2013, Barcelona, Spain, 21-25 October 2013. New York, NY, United States: ACM. doi: 10.1145/2502081.2502103

  • Li, Peng, Chen, Ling, Li, Xue and Wen, Junhao (2013). RNRank: Network-based ranking on relational tuples. 2013 International Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Beijing, Peoples R China, 3 - 9 August 2013. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-04048-6_13

  • Wang, Sen, Yang, Yi, Ma, Zhigang, Li, Xue, Pang, Chaoyi and Hauptmann, Alexander G. (2012). Action recognition by exploring data distribution and feature correlation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, United States, 16-21 June 2012. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/CVPR.2012.6247823

  • Cai, Hongyun, Huang, Zi, Shao, Jie and Li, Xue (2012). Context sensitive tag expansion with information inference. 17th International Conference on Database Systems for Advanced Applications, DASFAA 2012, Busan, South Korea, 15-19 April 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-29038-1_32

  • Hussein, Asmaa S., Omar, Wail M., Li, Xue and Ati, Modafar (2012). Efficient Chronic Disease Diagnosis prediction and recommendation system. 2012 IEEE EMBS International Conference on Biomedical Engineering and Sciences (IECBES), Langkawi, Malaysia, 17-19 December 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/IECBES.2012.6498117

  • Unankard, Sayan, Chen, Ling, Li, Peng, Wang, Sen, Huang, Zi, Sharaf, Mohamed A. and Li, Xue (2012). On the prediction of re-tweeting activities in social networks – a report on WISE 2012 Challenge. 13th International Conference on Web Information Systems Engineering (WISE 2012), Paphos, Cyprus, 28 - 30 November 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-35063-4_61

  • Nahar, Vinita, Unankard, Sayan, Li, Xue and Pang, Chaoyi (2012). Sentiment analysis for effective detection of cyber bullying. 14th Asia-Pacific Web Conference, APWeb 2012, Kunming, China, 11-13 April 2012. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-29253-8_75

  • Gollapalli, Mohammed, Li, Xue, Wood, Ian and Governatori, Guido (2011). Approximate record matching using hash grams. 2011 IEEE 11th International Conference on Data Mining (ICDM 2011), Vancouver Canada, 11-14 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDMW.2011.33

  • He, Jiazhen, Zhang, Yang, Li, Xue and Wang, Yong (2011). Bayesian classifiers for positive unlabeled learning. 12th International Conference on Web-Age Information Management, WAIM 201, Wuhan, China, 14 - 16 September 2011. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-23535-1_9

  • Thien Wan, Au, Sadiq, Shazia and Li, Xue (2011). Exploratory study on learners' experience in an eLearning system. 17th Americas Conference on Information Systems (AMCIS 2011), Detroit, MI, United States, 4-7 August 2011. Atlanta, GA, United States: Association for Information Systems.

  • Wan, Au Thien, Sadiq, Shazia and Li, Xue (2011). Exploratory study on learners' experience in an elearning system. 17th Americas Conference on Information Systems 2011, AMCIS 2011, Detroit, Michigan, August 4-8, 2011.

  • Gollapalli, Mohammed, Li, Xue, Wood, Ian and Governatori, Guido (2011). Ontology guided data linkage framework for discovering meaningful data facts. 7th International Conference on Advanced Data Mining and Applications (ADMA 2011), Beijing, China, 17-19 December 2011. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-25856-5_19

  • Li, Xue and Chen, Ling (2011). Recommendations based on network analysis. 2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011, Jakarta, Indonesia, 17-18 December 2011. Piscataway, NJ, United States: IEEE.

  • Li, Guohe, Wu, Weijiang, Li, Hongqi and Li, Xue (2011). Selection of continuous features based on distribution of objects. 2011 3rd International Workshop on Intelligent Systems and Applications, ISA 2011, Wuhan, China, 28-29 May 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISA.2011.5873248

  • Zhong, Jiang, Deng, Xiongbing, Liu, Jie, Li, Xue and Liang, Chuanwei (2010). A novel Chinese text feature selection method based on probability latent semantic analysis. The Seventh International Symposium on Neural Networks (ISNN 2010), Shangai, China, 6-9 June, 2010. Berlin & Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-13318-3_35

  • Qin, XJ, Zhang, Y, Li, X and Wang, Y (2010). Associative classifier for uncertain data. 11th International Conference on Web-Age Information Management (WAIM 2010), Jiuzhaigou, China, 15-17 July 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-14246-8_66

  • Pan, SR, Wu, KA, Zhang, Y and Li, X (2010). Classifier ensemble for uncertain data stream classification. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2010), Hyderabad, India, 21-24 June 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-13657-3_52

  • He, Jiazhen, Zhang, Yang, Li, Xue and Wang, Yong (2010). Naive Bayes classifier for positive unlabeled learning with uncertainty. The Tenth SIAM International Conference on Data Mining (SDM10), Columbus, Ohio, United States, 29 April - 1 May 2010. Philadelphia, PA, United States: Society for Industrial and Applied Mathematics (SIAM). doi: 10.1137/1.9781611972801.32

  • Wan, Au Thien, Sadiq, Shazia and Li, Xue (2010). On improving learning outcomes through sharing of learning experiences. 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010, Sousse, Tunisia, 5-7 July 2010. Piscataway, NJ, United States: IEEE Computer Society Conference Publishing Services (CPS). doi: 10.1109/ICALT.2010.134

  • Mahinderjit-Singh, Manmeet and Li, Xue (2009). Computational model for trust management in RFID supply chains. The 2009 IEEE International Symposium on Trust, Security and Privacy for Pervasive Applications, Macau, China, 12-15 October 2009. Piscataway NJ, USA: IEEE. doi: 10.1109/MOBHOC.2009.5336926

  • Huanh, Zi, Shen, Heng Tao, Song, Dawei, Li, Xue and Rueger, Stefan (2009). Dimension-specific search for multimedia retrieval. 14th International Conference, DASFAA 2009, Brisbane, Australia, 21-23 April 2009. Berlin, Germany; New York, U.S.A.: Springer. doi: 10.1007/978-3-642-00887-0

  • Au, Thien Wan, Sadiq, Shazia and Li, Xue (2009). Learning from experience: Can e-learning technology be used as a vehicle?. ICEL 2009: 4th International Conference on e-Learning, Toronto, Canada, 16-17 June 2009. Reading, U.K.: Academic Publishing.

  • Au, Thien Wan, Sadiq, Shazia and Li, Xue (2009). Learning from experience: can e-learning technology be used as a vehicle?. 4th International Conference on e-Learning, ICEL 2009, Toronto, Canada, 16-17 July 2009.

  • Li, Chen, Zhang, Yang and Li, Xue (2009). OcVFDT: One-class very fast decision tree for one-class classification of data streams. 3rd International Workshop on Knowledge Discovery from Sensor Data, SensorKDD'09 in Conjunction with the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD-09, Paris, France, 28 June 2009. New York, NY United States: ACM Press. doi: 10.1145/1601966.1601981

  • Dingyi Chen, Xue Li, Jing Liu and Xia Chen (2009). Ranking-Constrained Keyword Sequence Extraction from Web Documents. 20th Australasian Database Conference (ADC 2009), Wellington, New Zealand, Jan 2009. NSW, Aust: Australian Computer Society.

  • Mahinderjit-Singh, Manmeet and Li, Xue (2009). Trust framework for RFID tracking in supply chain management. 3rd International Workshop on RFID Technology - Concepts, Applications, Challenges, Milan, Italy, 6-7 May 2009. Portugal: INSTICC Press.

  • Natwichai, J., Sun, X. and Xue, Li (2008). A heuristic data reduction approach for associative classification rule hiding. PRICAI 2008: Tenth Pacific Rim International Conference on Artificial Intelligence, Hanoi, Vietnam, 15-19 December 2008. Berlin, Germany: Springer Verlag. doi: 10.1007/978-3-540-89197-0_16

  • Zhu, Y., Ye, M., Liu, N., Zhao, X. and Li, X. (2008). An Intrinsic Subsequence Decomposition Algorithm for Network Intrusion Detection. Fourth International Conference on Natural Computation, 2008, Jinan, PR China, 18-20 Oct 2008. Los Alamatis, California: IEEE Computer Society. doi: 10.1109/ICNC.2008.101

  • Harnsamut, N., Natwichai, J., Sun, X. and Li, X. (2008). Data Quality in Privacy Preservation for Associative Classification. Fourth International Conference on Advanced Data Mining and Applications (ADAMA 2008), Chengu, China, 8-10 Oct 2008. Berlin Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-540-88192-6_12

  • Natwichai, J., Sun, X. and Li, X. (2008). Data reduction approach for sensitive associative classification rule hiding. Database Technologies 2008, Wollongong, Australia, 22-25 Jan 2008. Sydney: Australian Computer Soc Inc.

  • Nguyen, Son N., Orlowska, Maria E. and Li, Xue (2008). Graph mining based on a data partitioning approach. Australasian Database Conference (ADC2008), Wollongong, Australia, 22-25 January 2008. Sydney, Australia: Australian Computer Society.

  • Zhang, Y., Li, X. and Orlowska, M. E. (2008). One-class classification of text streams with concept drift. IEEE International Conference on Data Mining Workshops 2008 (ICDMW '08), Pisa, Italy, 15-19 December 2008. Piscataway, NJ, U.S.A.: IEEE. doi: 10.1109/ICDMW.2008.54

  • Ma, S., Li, X., Ding, Y. and Orlowska, M. (2007). A recommender system with interest-drifting. 8th International Conference on Web Information Systems Engineering, Nancy, France, 3-7 December 2007. Berlin, Germany: Springer-Verlag. doi: 10.1007/978-3-540-76993-4_55

  • Wang, Qing, Dong, Zhao Yang, Li, X.ue, Zhao, Junhua and Wong, Kit Po (2007). An effective approach to predicting electricity market price spikes. 2007 IEEE Power Engineering Society General Meeting, Tampa, Florida, USA, 24-28 June 2007. Piscataway, NJ, United States: IEEE. doi: 10.1109/PES.2007.385852

  • Ye, Mao, Gao, Zengan and Li, Xue (2007). Blind separation of positive signals by using genetic algorithm. 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 3-7 June, 2007. Germany: Springer-Verlag. doi: 10.1007/978-3-540-72395-0_91

  • Sun, X., Chang, M., Li, X. and Orlowska, M. (2007). Discovering correlated items in data streams. 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2007), Nanjing, China, 22-25 May 2007. Berlin, Germany: Springer-Verlag. doi: 10.1007/978-3-540-71701-0_27

  • Zhao, Jun Hua, Li, Xue and Dong, Zhao Yang (2007). Online rare events detection. 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, Nanjing, May 22, 2007-May 25, 2007. doi: 10.1007/978-3-540-71701-0_126

  • Ali, Mohsin, Dong, Zhao Yang, Zhang, Pei and Li, Xue (2007). Probabilistic transient stability analysis using grid computing technology. 2007 IEEE Power Engineering Society General Meeting, Tampa, Florida, USA, 24-28 June, 2007. Piscataway, NJ, United States: IEEE. doi: 10.1109/PES.2007.385837

  • Derakhshan, Roozbeh, Orlowska, Maria E. and Li, Xue (2007). RFID data management: Challenges and opportunities. IEEE International Conference on RFID 2007, Grapevine, Texas, USA, 26-28 March 2007. Piscatawa, NJ, United States: IEEE. doi: 10.1109/RFID.2007.346166

  • Ye, M., Li, X. and Orlowska, M. (2007). Supervised dimensionality reduction on streaming data. Fourth International Conference on Fuzzy Systems and Knowledge Discovery 2007 (FSKD 2007), Haikou, China, 24-27 August 2007. Los Alamitos, CA, U.S.A.: IEEE Computer Society. doi: 10.1109/FSKD.2007.548

  • Ali, M., Dong, Z. Y., Li, X. and Zhang, P. (2006). A grid computing based approach for probabilistic load flow analysis. 7th IET International Conference on Advances in Power System Control, Operation and Management, APSCOM 2006, , , October 30, 2006-November 2, 2006. IEE. doi: 10.1049/cp:20062127

  • Ali, M, Dong, Z Y, Li, X and Zhang, P. (2006). A grid computing based approach for probablisitic load flow analysis. 7th International Conference on Advances in Power System Control, Operation and Management, Hong Kong, 30 October - 2 November, 2006. Hong Kong: The Institution of Engineering and Technology Hong Kong.

  • Bray, J., Verma, B,, Li, X. and He, W. (2006). A neural network based technique for automatic classification of road cracks. International Joint conference on Neural Networks 2006 (IJCNN '06), Vancouver, Canada, 16-21 July 2006. Piscatawa, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/IJCNN.2006.246782

  • Xu, Z., Ali, M., Dong, Z. Y. and Li, X. (2006). A novel grid computing approach for probabilistic small signal analysis. 2006 IEEE Power Engineering Society General Meeting, Montreal, Canada, 18-22 June, 2006. Piscataway, NJ, United States: IEEE. doi: 10.1109/pes.2006.1709449

  • Natwichai, J., Li, X and Orlowska, M E (2006). A reconstruction-based algorithm for classification rules hiding. 17th Australasian Database Conference (ADC2006), Tasmania, Australia, 16-19 January, 2006. New South Wales: Australian Computer Society Inc..

  • Li, Xue, Zaïane, Osmar R. and Li, Zhanhuai (2006). Advanced Data Mining and Applications: Second International Conference, ADMA 2006 Xi'an, China, August 14-16, 2006 Proceedings. Springer Verlag.

  • Yan, Xin, Song, Dawei and Li, Xue (2006). Concept-based document readability in domain specific information retrieval. CIKM'06 Fifteenth Conference on Information and Knowledge Management, Arlington, Virginia, USA, 5-11 November 2006. USA: ACM. doi: 10.1145/1183614.1183692

  • Ye, Mao, Li, Xue, Yang, Chengfu and Gao, Zengan (2006). Convergence analysis of a discrete-time single-unit gradient ICA algorithm. Springer Verlag. doi: 10.1007/11759966_168

  • Yan, X, Li, X and Song, (2006). Document generality: its computation for ranking. Seventeenth Australiasian Database Conference (ADC2006), Hobart, Australia, 16-19 January, 2006. Tasmania, Australia: Australian Computer Society Inc..

  • Zhao, Jun Hua, Dong, Zhao Yang and Li, Xue (2006). Electricity price forecasting with effective feature preprocessing. 2006 IEEE Power Engineering Society General Meeting, Montreal Canada, 18-22 June 2006. Piscataway, NJ United States: IEEE. doi: 10.1109/PES.2006.1709407

  • Sun, X., Orlowska, M E and Li, X (2006). Finding frequent itemsets in high-speed data streams. 2006 6th SIAM International Conference on Data Mining, Maryland, USA, 20-22 April, 2006. USA: Society for Industrial & Applied Mathematics (SIAM).

  • Ali, M., Dong, Z. Y., Li, X. and Zhang, P. (2006). RSA-Grid: A grid computing based framework for power system reliability and security analysis. 2006 IEEE Power Engineering Society General Meeting, Montreal, Canada, 18-22 June 2006. Piscataway, NJ, United States: IEEE. doi: 10.1109/pes.2006.1709374

  • Ding, Y. H., Li, X and Orlowska, M E (2006). Recency-based collaborative filtering. 17th Australasian Database Conference (ADC2006), Tasmania, Australia, 16-19 January 2006. New South Wales: Australian Computer Society.

  • Zhao, J., Dong, Z. Y., Li, X. and Wong, K.P (2005). A general method for electricity market price spike analysis. IEEE Power Engineering Society General Meeting, San Francisco, USA, 12-16 July 2005. USA: IEEE.

  • Ali, M., Dong, Z. Y., Li, X. and Zhang, P. (2005). Applications of grid computing in power systems. Australasian Universities Power Engineering Conference 2005, Hobart, Australia, 25-28 September 2005. Hobart, Australia: AUPEC 2005.

  • Barajas, J. and Li, X. (2005). Collaborative filtering on data streams. 9th European Conference on Principles & Practice of Knowledge Discovery on Databases, Porto, Portugal, 3-7 October, 2005. Germany: Springer-Verlag. doi: 10.1007/11564126_42

  • Chen, D., Li, X., Dong, Z. Y. and Chen, X. (2005). Determining the fitness of a document model by using conflict instances. 16th Australasian Database Conference (ADC 2005), Newcastle, Australia, 31 January - 3 February 2005. Sydney, Australia: Australian Computer Society Inc..

  • Liu, Z., Li, X. and Dong, Z. Y. (2005). Direct fingerprinting on multicasting compressed video. 11th International conference on Multimedia Modelling, MMM05, Melbourne, Australia, 12-14 January, 2005. Piscataway NJ USA: IEEE Computer Society. doi: 10.1109/MMMC.2005.35

  • Yan, X., Li, X. and Song, D. (2005). Document re-ranking by generality in bio-medical information retrieval. 6th International Conference on Web Information Systems Engineering, New York, USA, 20-22 November, 2005. Berlin, Germany: Springer-Verlag. doi: 10.1007/11581062_28

  • Chen, D., Li, X., Dong, Z. Y. and Chen, X. (2005). Effectiveness of document representation for classification. 7th International Conference on Data Warehousing and Knowledge Discovery, Copenhagen, Denmark, 22-26 August, 2005. Berlin Heidelberg, Germany: Springer. doi: 10.1007/11546849

  • Ali, Mohsin, Li, Xue and Dong, Zhao Yang (2005). Efficient spatial clustering algorithm using binary tree. Sixth International Conference on Intelligent Data Engineering and Automated Learning - IDEAL '05, Brisbane, Australia, 6-8 July 2005. Berlin, Germany: Springer. doi: 10.1007/11508069_39

  • Sun, Xingzhi, Orlowska, Maria E. and Li, Xue (2005). Finding temporal features of event-oriented patterns. The 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 05), Hanoi, Vietnam, 18-20 May 2005. Berlin, Germany: Springer. doi: 10.1007/11430919_91

  • Natwichai, Juggapong, Li, Xue and Orlowska, Maria E. (2005). Hiding Classification Rules for Data Sharing with Privacy Preservation. 7th International Conference on Data Warehousing and Knowledge Discovery, Copenhagen, Denmark, 22-26 August, 2005. Germany: Springer. doi: 10.1007/11546849_46

  • Ding, Yi and Li, Xue (2005). Time weight collaborative filtering. 14th ACM International Conference on Information and Knowledge Management (CIKM'05), Bremen, Germany, 31 October - 5 November 2005. New York, United States: Association for Computing Machinery. doi: 10.1145/1099554.1099689

  • Yan, Xin, Li, Xue and Song, Daqei (2004). A Correlation Analysis on LSA and HAL Semantic Space Models. First International Symposium, CIS 2004, Shanghai, China, 16-18 December, 2004. Berlin: Springer-Verlag. doi: 10.1007/b104566

  • Liu, Zeng, Li, Xue and Dong, Zhaoyang (2004). A lightweight encryption algorithm for mobile online multimedia devices. The Fifth International Conference on Web Information Systems Engineering (WISE 2004), Brisbane, Australia, 22-24 November 2004. Berlin, Germany: Springer-Verlag.

  • Chen, X., Orlowska, M. E. and Li, X. (2004). A new framework of privacy preserving data sharing. The Fourth IEEE International Conference on Data Mining (ICDM '04), Brighton, U.K., 1-4 November 2004. Los Alamitos, CA, U.S.A.: IEEE Computer Society.

  • Liu, Zheng, Li, Xue and Dong, Zhaoyang (2004). A sensor-based multimedia authentication system. The 2004 IEEE International Conference on Multimedia and Expo (ICME 2004), Taipei, Taiwan, 27-30 June 2004. Los Alamitos, CA, U.S.A.: IEEE Communications Society. doi: 10.1109/ICME.2004.1394357

  • Liu, Z., Li, X. and Dong, Z. Y. (2004). Enhancing security of frequency domain video encryption. The Twelfth ACM International Conference on Multimedia, New York, 10-16 October, 2004. New York: The Association for Computing Machinery. doi: 10.1145/1027527.1027597

  • Sun, Xingzhi, Orlowska, Maria E.. and Li, Xue (2004). Finding negative event oriented patterns in long temporal sequences. The Eighth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2004), Sydney, Autstralia, 26-28 May 2004. Berlin; Heidelberg, Germany: Springer-Verlag. doi: 10.1007/b97861

  • Chen, D., Li, X., Dong, Z. Y. and Smith, P.A. (2004). Interactive email filtering: Learning from misclassified examples. The 2004 IEEE Conference on Cybernetics and Intelligent Systems, Singapore, 1-3 December, 2004. Los Alamitos, CA, U.S.A.: IEEE. doi: 10.1109/ICCIS.2004.1460736

  • Natwichai, Juggapong and Li, Xue (2004). Knowledge maintenance on data streams with concept drifting. First International Symposium on Computational and Information Science (CIS 2004), Shanghai, China, 16-18 December 2004. Berlin; Heidelberg, Germany: Springer Berlin / Heidelberg. doi: 10.1007/b104566

  • Natwichai, Juggapong and Li, Xue (2004). Knowledge maintenance on data streams with concept drifting. CIS 2004: Computational and Information Science , Shanghai, China, 16-18 December, 2004. Berlin, Germany: Springer Verlag. doi: 10.1007/978-3-540-30497-5_110

  • Liu, Zheng and Li, Xue (2004). Motion vector encryption in multimedia streaming. The Tenth International Conference on Multimedia Modelling, Brisbane, Australia, 5-7 January 2004. Los Alamitos, California, U.S.A.: IEEE Computer Society. doi: 10.1109/MULMM.2004.1264968

  • Liu, Z., Li, X. and Dong, Z. Y. (2004). Multimedia authentication with sensor-based watermarking. The Multimedia and Security Workshop 2004, Magdeburg, Germany, 20-21 September, 2004. New York: The Association for Computing Machinery. doi: 10.1145/1022431.1022458

  • Sorbello, M., Dong, Z. Y. and Li, X. (2004). On the development of a web electricity market simulator. The Australasian Universities Power Engineering Conference 2004, Brisbane, 26-29 September, 2004. Brisbane: AUPEC.

  • Chen, D. and Li, X. (2004). PLD: A distillation algorithm for misclassified documents. The Fifth International Conference on Web-Age Information Management (WAIM 2005), Dalien, China, 15-17 July 2004. Berlin, Germany: Springer-Verlag.

  • Li, Xue (2004). Reflective web interface agent. APWeb 2004: Advanced Web Technologies and Applications, Hangzhou, China, 14-17 April, 2004. Berlin, Germany: Springer Verlag. doi: 10.1007/978-3-540-24655-8_15

  • Li, Xue (2004). Reflective web interface agent. The Sixth Asia Pacific Web Conference (APWEB'04), Hangzhou, China, 14-17 April 2004. Berlin, Germany: Springer-Verlag. doi: 10.1007/b96838

  • Li, X., Huang, W., Jiang, F. and Xu, D.M. (2003). How can managers adopt and use electronic communication media more effectively? An exploratory study. The Seventh World Multi-Conference on Systemics, Cybernetics and Informatics, Orlando, Florida, 27-20 July, 2003. Orlando, Florida: The International Institute of Information Systems.

  • Zakos, J., Verma, B., Li, X. and Kulkarni, S. (2003). Intelligent encoding of concepts in web development retrieval. Fifth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2003), Xian, China, 27-30 September 2003. Los Alamitos, U.S.A.: IEEE Computer Society. doi: 10.1109/ICCIMA.2003.1238103

  • Sun, X., Orlowska, M. E. and Li, X. (2003). Introducing uncertainty into pattern discovery in temporal event sequences. Third IEEE International Conference on Data Mining 2003 (ICDM 2003), Melbourne, Australia, 19-22 November 2003. Piscataway, NJ, U.S.A.: The Institute of Electrical and Electronics Engineers.

  • Li, X., He, W., Dong, Z. Y., Verma, B., Yu, K., Koh, T. C. and Ng, C. W. (2003). Real time web vehicle classifier. The Seventh International Symposium on Digitial Processing and Communication Systems, The Gold Coast, 8-11 December, 2003. Wollongong: The University of Wollongong.

  • Dong, Z. Y., Li, X., Xu, Z. and Teo, K. L. (2003). Weather depenent electricity market forecasting with neural networks, wavelet and data mining techniques. The Australasian Universities Power Engineering Conference, Christchurch, New Zealand, 28 September-1 October, 2003. New Zealand: AUPEC.

  • Pek, E., Li, X. and Liu, Y. (2003). Web wrapper validation. 5th Asia-Pacific Web Conference, Xian, China, 23-25 April 2003. Berlin, Germany: Springer Verlag. doi: 10.1007/3-540-36901-5_40

  • Li, X. and Chen, P. (2002). Automatic assessment of e-busineses. International Conference on e-Business, Beijing, 23-26 May, 2003. Beijing: Beijing Institute of Technology Press.

  • Li, X. and Foo, I. P. (2002). Intelligent business portal: Availability vs. applicability. International Conference on e-Business, Beijing, 23-26 May, 2003. Beijing: Beijing Institute of Technology Press.

  • Li, X., Huang, W., Gandha, G., Yao, X.G. and Huang, H.S. (2002). What web features and functions are used by Australian corporations in their websites? A conceptual framework and an empirical investigation. 2002 Information Resources Management Association International Conference, Seattle, 19-22 May, 2002. Hershey: Idea Group Publishing.

  • Li, X. (2001). Building intelligent business portals. Asia Pacific Web Conference 2001, Changsha, China, 21-22 November, 2001. Beiging, China: Publishing House of Electronics Industry.

  • Li, X. and Huang, W. (2001). On the assessment of commercial website: An expert system approach. Twelfth Australasian Conference on Information Systems, Coffs Harbour, NSW, 4-7 December, 2001. Coffs Harbour, NSW: Southern Cross University.

Edited Outputs

Other Outputs

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Description:

    Traditional database queries are used to search for facts from structured database such as RDB (Relational Databases) to satisfy user search conditions. With big data currently available in many ways such as structured and unstructured multi-modalities, user queries should be constructed not only for searching facts, but also for searching patterns, emerging events, and outliers from available big data. This PhD research is to propose a new type of query language that can query on analytic results , to satisfy user requirements for informed decision support. In order to make such a language to be implementable on general big dataset, this PhD research will also define and design a framework that can answer declarative analytic queries by a data-driven approach to apply transparent machine learning algorithms in order to discover unexpected patterns, emerging trends, various correlations from big data. The challenges of this research will be on how to use an end-to-end black-box mechanism to provide big data analytic services to make big data available for general queries beyond classical data warehousing technologies.

    Background:

    In classical DSS systems based on data warehouses and OLAP operations, the queries such as Canned and Continuous Queries would not involve procedural operations that can reflect the dynamic parameters of queries. The operators such as Role-Up, Drill-Down, Slice/Dice, Cube, Pivoting etc, cannot reflect the context of the query objects in their business context. This PhD research will try to introduce more flexible analytical data manipulation operations based on machine learning algorithms that can provide end-to-end queries for strategic DSS with baselines.

  • Description:

    Artificial Intelligence (AI) applications are mostly based on the first-order thinking that is resoning based on deduction, abduction, induction, or eduction. In this way, AI is limited and unable to discover the First Principles such as those in sciences and complex Math Equitions, Laws in Physics and Chemistry. However, this should not prevent AI to be used together with the First Principles in those descovery projects. This PhD research is to design an architecture of AI Application platform that can use First Princile in AI to speed up the human trial-and-error process of experiments, to use First Principle in a more intelligent way to converge an optimazation process which has a large number of iterations faster and scalable for human's research problems.

  • Description:

    Predictive data analytics usually involves Big Data that is distributed in different locations and owned by different organizations, such as the Taxation Office Data, Boarder-Control Customs Data, Crime-Stop Police Data, and Social Security Data. The organizations are legally responsible for the privacy preservation of their data which is of highly risk and sensitive. However, this should not prevent the sharing of those de-identified, privacy preserved data sets for the predictions of pending social-economic events, emerging trends, patterns of relationships, or correlations among entities. Currently, there are many algorithms that can preserve privacy for computing data from multiple owners, such as SMC (secure multi-party computation), Differential Privacy algorithms. However, the predictive tasks often require to use all original raw data for the learning. This would involve the individual organizations to conduct local learning tasks and contribute to global learning with their local models, instead of their sensitive data. Federated learning therefore coming to being as a promising and useful approach to learn from individual datasets and producing a general model for the required predicting tasks. This project is to research on the Federated Learning algorithms that can deal with large distributed, sensitive datasets and derive a computational model to predict some pre-defined tasks. The challenges of this project would be the following three issues in one solution, i.e., data shareability, data privacy, and computational utility.

    Key Terms: Federated Learning, Deep Learning, Distributed Database Technology, Privacy Preservation, Mathematical Modelling, Data Shareability, Computational Utility