Lin Yue

Dr Lin Yue

Lecturer

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Dr Lin Yue earned her PhD from Jilin University, with part of her doctoral studies completed as a joint PhD candidate at the University of Queensland. From 2014 to 2015, she was a member of the Data Science Group at the University of Queensland. Throughout her academic career, she has held positions at several esteemed institutions, including Northeast Normal University, the University of Queensland, and the University of Newcastle.

Dr Yue's research is centered on Sequential Data Analysis and its diverse applications. Her work spans multiple domains, including Medical Data Analytics, EEG Data Analysis, Brain-Computer Interfaces, Social Media Data Analytics, and Sentiment Analysis.

Dr Yue is recognized for her collaborative research efforts, working closely with professionals across academia, government, and professional organizations. Her work has been supported by numerous internal and external research grants.

  • Journals
    Year Citation
    2024 Xu, Y., Li, T., Yang, Y., Chen, W., & Yue, L. (2024). An adaptive category-aware recommender based on dual knowledge graphs. Information Processing and Management, 61(3), 14 pages.
    DOI Scopus1
    2024 Han, X., Chu, Y., Wang, K., Wang, L., Yue, L., & Ding, W. (2024). TAILOR: InTer-feAture distinctIon fiLter fusiOn pRuning. Information Sciences, 665, 120229.
    DOI
    2023 Shi, Z., Wang, S., Yue, L., Zhang, Y., Adhikari, B. K., Xue, S., . . . Li, X. (2023). Dual-core mutual learning between scoring systems and clinical features for ICU mortality prediction. Information Sciences, 637, 13 pages.
    DOI Scopus1
    2023 Chen, W., Zhang, W. E., & Yue, L. (2023). Death comes but why: A multi-task memory-fused prediction for accurate and explainable illness severity in ICUs. World Wide Web, 26(6), 4025-4045.
    DOI Scopus1
    2023 Guo, L., Wang, L., Han, X., Yue, L., Zhang, Y., & Gao, M. (2023). ROCM: A Rolling Iteration Clustering Model Via Extracting Data Features. Neural Processing Letters, 55(4), 3899-3922.
    DOI
    2023 Amagasa, T., Calvanese, D., Han, X., Li, B., Tao, C., & Yue, L. (2023). Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13421 LNCS, v-vi.
    2023 Li, B., Yue, L., Tao, C., Han, X., Calvanese, D., & Amagasa, T. (2023). Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13422 LNCS, v-vi.
    2023 Amagasa, T., Calvanese, D., Han, X., Li, B., Tao, C., & Yue, L. (2023). Preface. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13423 LNCS, v-vi.
    2022 Zhang, Y., Peng, T., Han, R., Han, J., Yue, L., & Liu, L. (2022). Synchronously tracking entities and relations in a syntax-aware parallel architecture for aspect-opinion pair extraction. Applied Intelligence, 52(13), 15210-15225.
    DOI Scopus6
    2022 Peng, T., Han, R., Cui, H., Yue, L., Han, J., & Liu, L. (2022). Distantly Supervised Relation Extraction using Global Hierarchy Embeddings and Local Probability Constraints. Knowledge-Based Systems, 235, 107637.
    DOI Scopus16
    2022 Wang, Y. D., Chen, W. T., Pi, D. C., & Yue, L. (2022). Adaptive Multi-Hop Reading on Memory Neural Network with Selective Coverage Mechanism for Medication Recommendation. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 50(4), 943-953.
    DOI Scopus1
    2021 Wang, Y., Chen, W., Pi, D., & Yue, L. (2021). Adversarially regularized medication recommendation model with multi-hop memory network. Knowledge and Information Systems, 63(1), 125-142.
    DOI Scopus23 WoS16
    2021 Yue, L., Shen, H., Wang, S., Boots, R., Long, G., Chen, W., & Zhao, X. (2021). Exploring BCI control in smart environments: intention recognition via EEG representation enhancement learning. ACM Transactions on Knowledge Discovery from Data (TKDD), 15(5), 1-20.
    DOI Scopus17 WoS8
    2021 Shi, Z., Wang, S., Yue, L., Pang, L., Zuo, X., Zuo, W., & Li, X. (2021). Deep dynamic imputation of clinical time series for mortality prediction. Information Sciences, 579, 607-622.
    DOI Scopus13
    2020 Shi, Z., Zuo, W., Liang, S., Zuo, X., Yue, L., & Li, X. (2020). IDDSaM: an Integrated Disease Diagnosis and Severity assessment Model for Intensive Care Units. IEEE Access, 8, 15423-15435.
    DOI Scopus8
    2020 Zhang, Y., Shi, Z., Zuo, W., Yue, L., Liang, S., & Li, X. (2020). Joint Personalized Markov Chains with social network embedding for cold-start recommendation. Neurocomputing, 386, 208-220.
    DOI Scopus34
    2020 Yue, L., Tian, D., Chen, W., Han, X., & Yin, M. (2020). Deep learning for heterogeneous medical data analysis. World Wide Web, 23(5), 2715-2737.
    DOI Scopus54 WoS27
    2019 Yue, L., Chen, W., Li, X., Zuo, W., & Yin, M. (2019). A survey of sentiment analysis in social media. Knowledge and Information Systems, 60(2), 617-663.
    DOI Scopus335 WoS181
    2018 Zhao, X., Li, J., Wang, R., He, F., Yue, L., & Yin, M. (2018). General and species-specific lysine acetylation site prediction using a bi-modal deep architecture. IEEE Access, 6, 63560-63569.
    DOI Scopus6
    2018 Yue, L., Sun, X. X., Gao, W. Z., Feng, G. Z., & Zhang, B. Z. (2018). Multiple Auxiliary Information Based Deep Model for Collaborative Filtering. Journal of Computer Science and Technology, 33(4), 668-681.
    DOI Scopus17
    2017 Yang, Y., Xu, Y., Han, J., Wang, E., Chen, W., & Yue, L. (2017). Efficient traffic congestion estimation using multiple spatio-temporal properties. Neurocomputing, 267, 344-353.
    DOI Scopus43
    2017 Yue, L., Shi, Z., Han, J., Wang, S., Chen, W., & Zuo, W. (2017). Multi-factors based sentence ordering for cross-document fusion from multimodal content. Neurocomputing, 253, 6-14.
    DOI Scopus2
    2015 Yue, L., Zuo, W., Peng, T., Wang, Y., & Han, X. (2015). A fuzzy document clustering approach based on domain-specified ontology. Data and Knowledge Engineering, 100, 148-166.
    DOI Scopus25
    2015 Guo, L., Zuo, W., Peng, T., & Yue, L. (2015). Text Matching and Categorization: Mining Implicit Semantic Knowledge from Tree-Shape Structures. Mathematical Problems in Engineering, 2015, 1-9.
    DOI Scopus4
    2014 Yue, L., Zuo, W., Feng, L., & Guo, L. (2014). OMFM: A framework of object merging based on fuzzy multisets. Mathematical Problems in Engineering, 2014, 1-15.
    DOI Scopus1
    2012 Yang, X., Zou, C., Yue, L., & Gao, R. (2012). Research on food complains document classification based-on topic. Journal of Software, 7(8), 1687-1693.
    DOI Scopus1
    2012 Yang, X. Q., Yue, L., Ma, Z. Q., Lv, Y. H., & Martinez, F. S. (2012). An ontology-driven approach based on fuzzy equivalence relation for document clustering analysis. ICIC Express Letters, 6(5), 1321-1327.
    Scopus1
    2011 Yang, X., Yue, L., Liu, C., Zou, C., & Tian, Y. (2011). A knowledge-driven approach for document clustering. ICIC Express Letters, Part B: Applications, 2(5), 1123-1129.

  • Book Chapters
    Year Citation
    2023 Yue, L., Zhang, Y., Zhao, X., Zhang, Z., & Chen, W. (2023). Improving Motor Imagery Intention Recognition via Local Relation Networks. In B. Li, L. Yue, C. Tao, X. Han, D. Calvanese, & T. Amagasa (Eds.), Web and Big Data (Vol. 13421 LNCS, pp. 345-356). Switzerland: Springer Nature Switzerland.
    DOI

  • Conference Papers
    Year Citation
    2024 Dong, C. G., Zheng, L. N., Chen, W., Zhang, W. E., & Yue, L. (2024). SWAP: Exploiting Second-Ranked Logits for Adversarial Attacks on Time Series. In Proceedings of the IEEE International Conference on Knowledge Graph (ICKG 2023) Vol. 25 (pp. 117-125). Online: IEEE.
    DOI
    2023 Shen, S., Xu, M., Yue, L., Boots, R., & Chen, W. (2023). Death Comes But Why: An Interpretable Illness Severity Predictions in ICU. In B. Li, L. Yue, C. Tao, X. Han, D. Calvanese, & T. Amagasa (Eds.), Proceedings International Joint Conference APWeb-WAIM 2022 Vol. 13421 LNCS (pp. 60-75). Nanjing, China: Springer Nature Switzerland.
    DOI Scopus1
    2023 Xu, Y., Zhang, Y., Yang, Y., Xu, H., & Yue, L. (2023). Duet Representation Learning with Entity Multi-attribute Information in Knowledge Graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14177 LNAI (pp. 32-45). Shenyang: Springer Science and Business Media Deutschland GmbH.
    DOI
    2023 Xu, Y., Yue, L., Xu, H., & Yang, Y. (2023). Learning Knowledge Representation with Entity Concept Information. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14179 LNAI (pp. 268-283). Shenyang: Springer Science and Business Media Deutschland GmbH.
    DOI
    2023 Wang, C., Peng, T., Zhang, Y., Yue, L., & Liu, L. (2023). AOPSS: A Joint Learning Framework for Aspect-Opinion Pair Extraction as Semantic Segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13422 LNCS (pp. 101-113). Nanjing: Springer Science and Business Media Deutschland GmbH.
    DOI
    2022 Zhang, M., Yue, L., & Xu, M. (2022). ESTD: Empathy Style Transformer with Discriminative Mechanism. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13726 LNAI (pp. 58-72). Brisbane, Queensland: Springer Science and Business Media Deutschland GmbH.
    DOI Scopus1
    2022 Zhao, Y., Yue, L., & Xu, M. (2022). A Boosting Algorithm for Training from Only Unlabeled Data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13726 LNAI (pp. 459-473). Brisbane Queensland: IEEE.
    DOI
    2022 Jiang, L., Zhang, W., Wang, Y., Luo, N., & Yue, L. (2022). Augmenting Personalized Question Recommendation with Hierarchical Information for Online Test Platform. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13087 LNAI (pp. 103-117). Brisbane, Australia: Springer.
    DOI Scopus4
    2022 Zhang, C., Zhang, Y., Mao, J., Chen, W., Yue, L., Bai, G., & Xu, M. (2022). Towards Better Generalization for Neural Network-Based SAT Solvers. In Pacific-Asia Conference on Knowledge Discovery and Data Mining Vol. 13281 LNAI (pp. 199-210). Online: Springer, Cham.
    DOI Scopus2
    2022 Qiu, Y., Chen, W., Yue, L., Xu, M., & Zhu, B. (2022). STCT: Spatial-Temporal Conv-Transformer Network for Cardiac Arrhythmias Recognition. In International Conference on Advanced Data Mining and Applications Vol. 13087 LNAI (pp. 86-100). Online: Springer, Cham.
    DOI Scopus6 WoS1
    2022 Zang, Y., Liu, Y., Chen, W., Li, B., Li, A., Yue, L., & Ma, W. (2022). GISDCN: A Graph-Based Interpolation Sequential Recommender with Deformable Convolutional Network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13246 LNCS (pp. 289-297). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
    DOI Scopus11
    2021 Wang, Y., Chen, W., Pi, D., Yue, L., Wang, S., & Xu, M. (2021). Self-Supervised Adversarial Distribution Regularization for Medication Recommendation.. In IJCAI (pp. 3134-3140). Virtual, Online: International Joint Conferences on Artificial Intelligen.
    Scopus21
    2021 Liu, C., Yang, Y., Yao, Z., Xu, Y., Chen, W., Yue, L., & Wu, H. (2021). Discovering Urban Functions of High-Definition Zoning with Continuous Human Traces. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management Vol. 72 (pp. 1048-1057). Virtual, Online: Association for Computing Machinery.
    DOI Scopus3
    2021 Wang, Y., Chen, W., Pi, D., Yue, L., Xu, M., & Li, X. (2021). Multi-hop Reading on Memory Neural Network with Selective Coverage for Medication Recommendation. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (pp. 2020-2029). Virtual, Online: Association for Computing Machinery.
    DOI Scopus5 WoS2
    2021 Yue, L., Tian, D., Jiang, J., Yao, L., Chen, W., & Zhao, X. (2021). Intention recognition from spatio-temporal representation of EEG signals. In M. Qiao, G. Vossen, S. Wang, & L. Li (Eds.), Databases Theory and Applications. ADC 2021 Vol. 12610 LNCS (pp. 1-12). Switzerland AG: Springer, Cham.
    DOI Scopus6 WoS4
    2019 Shi, Z., Zuo, W., Chen, W., Yue, L., Hao, Y., & Liang, S. (2019). DMMAM: Deep multi-source multi-task attention model for intensive care unit diagnosis. In Database Systems for Advanced Applications (DASFAA) Vol. 11447 (pp. 53-69). Handel, Switzerland: Springer, Cham.
    DOI Scopus6 WoS5
    2019 Chen, W., Yue, L., Li, B., Wang, C., & Sheng, Q. Z. (2019). DAMTRNN: a delta attention-based multi-task RNN for intention recognition. In International Conference on Advanced Data Mining and Applications Vol. LNAI 11888 (pp. 373-388). Dalian, China: Springer, Cham.
    DOI Scopus7 WoS9
    2019 Shi, Z., Chen, W., Liang, S., Zuo, W., Yue, L., & Wang, S. (2019). Deep interpretable mortality model for intensive care unit risk prediction. In J. Li, S. Wang, S. Qin, X. Li, & S. Wang (Eds.), Advanced Data Mining and Applications. ADMA 2019. Vol. 11888 (pp. 617-631). Dalian, China: Springer, Cham.
    DOI Scopus7 WoS4
    2019 Yue, L., Zhao, H., Yang, Y., Tian, D., Zhao, X., & Yin, M. (2019). A Mimic Learning Method for Disease Risk Prediction with Incomplete Initial Data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11448 LNCS (pp. 392-396). Springer International Publishing.
    DOI Scopus2
    2018 Zhang, Y., Zuo, W., Shi, Z., Yue, L., & Liang, S. (2018). Social Bayesian personal ranking for missing data in implicit feedback recommendation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11061 LNAI (pp. 299-310). Springer International Publishing.
    DOI Scopus4
    2018 Hao, Y., Zuo, W., Shi, Z., Yue, L., Xue, S., & He, F. (2018). Prognosis of thyroid disease using MS-apriori improved decision tree. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11061 LNAI (pp. 452-460). Springer International Publishing.
    DOI Scopus7
    2018 Chen, W., Wang, S., Zhang, X., Yao, L., Yue, L., Qian, B., & Li, X. (2018). EEG-based motion intention recognition via multi-task RNNs. In SIAM International Conference on Data Mining, SDM 2018 (pp. 279-287). Society for Industrial and Applied Mathematics.
    DOI Scopus81
    2017 Shi, Z., Zuo, W., Chen, W., Yue, L., Han, J., & Feng, L. (2017). User relation prediction based on matrix factorization and hybrid particle swarm optimization. In Proceedings of the 26th International Conference on World Wide Web Companion (pp. 1335-1341). Perth, Australia: ACM Digital.
    DOI Scopus11 WoS10
    2012 Yang, X., Wang, M., Fang, L., Yue, L., & Lv, Y. (2012). Research on domain-specific features clustering based spectral clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7332 LNCS (pp. 84-92). Springer Berlin Heidelberg.
    DOI Scopus1
Grant/Funding Project/Description Location Year
CESE Excellence Strategic Investment Scheme Digital Sentinels: Multidisciplinary Approach for Detecting Mental Health Signals in Social Media Australia 2024
CESE Conference Scheme The International Conference on Database Systems for Advanced Applications (DASFAA) Australia 2024
Fellowship Accelerator Scheme Detecting Sentimental Clues from Implicit Language Expressions Australia 2023
SIPS Course Development Funding Statistical Reasoning and Literacy Australia 2023
UON Start-up Funding Semi-supervised Federated Learning for Highly-Imbalanced Medical Data Analysis Australia 2022
SIPS Course Development Funding Predictive Analytics Australia 2022
UQ Early Career Researchers AI Collaborative Seed Funding Grant Towards Positive Emotion: Artificial Intelligence-based Expression Rephrasing Australia 2022
Ford Motor Company University Research Program (URP) UMN: Unmanned Mapless Navigation Based on Reinforcement Learning Sensor Network  USA 2020
National Natural Science Foundation of China Solving and Computing the Size of the Solution Space for High Dimensional SMT Formulas China 2020
Outstanding Sino-foreign Youth Exchange Program of China Association for Science and Technology Jilin Province, Total of 5 People  China 2019
Excellent Young Talents Fund Project of Jilin Province Research on Learning and Reasoning Model Based on Heterogeneous Medical Data China 2018-2019
Fundamental Research Funds for the Central Universities Research on Network Emergency Detection Based on Gradient Petri Nets China 2017-2018
Key Laboratory of Symbolic Computation and Knowledge Engineering of Jilin University, Ministry of Education, Open Fund Project Research on Prediction of Sensitive Events Based on Heterogeneous Social Media Data China 2017-2018

  • Current Higher Degree by Research Supervision (University of Adelaide)
    Date Role Research Topic Program Degree Type Student Load Student Name
    2024 Co-Supervisor Artificial intelligence-based diagnosis using multimodal information Doctor of Philosophy Doctorate Full Time Mr Liangwei Zheng
    2023 Co-Supervisor An efficient and robust deep learning framework for multi-scale feature fusion object detection Doctor of Philosophy Doctorate Full Time Mr Yibo Sun

  • Other Supervision Activities
    Date Role Research Topic Location Program Supervision Type Student Load Student Name
    2024 - ongoing Co-Supervisor Weakly Supervised Learning for Mental Health The University of Queensland - Doctorate Full Time Mingzhe Zhang
  • Position: Lecturer
  • Phone: 83132277
  • Email: lin.yue@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor Level Five
  • Room: 5.42
  • Org Unit: School of Computer and Mathematical Sciences
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