Huizhi Liang, Elly

• Software Tools

MemoryChat chatbot

• Datasets

HCU health claim dataset

• Book chapter

1. Yongqiang Zhao, Shirui Pan, Jia Wu, Huaiyu Wan, Huizhi Liang, Haishuai Wang, Huawei Shen (2020):
   IEEE Access Special Section Editorial: Advanced Data Mining Methods for Social Computing. IEEE Access 8: 228598-228604 G1

• Journal Papers 

1. Shufei Duan, Yuting Yan, Qianrong Guo, Fujiang Li, Huizhi Liang (2025). Lightweight EEG Phase Prediction Based on Channel Attention and Spatio-Temporal Parallel Processing. Brain Sciences (PDF).
2. Fan Jiang, Qiuyue Dong, Emilio Fernandez-Egea, Rudolf N Cardinal, Xinyu Li, Huizhi Liang, Wenbo Song, Alimu Dayimu, Haibo Wang, Lei Xu, Shanquan Chen (2025) Identifying modifiable factors and their joint associations on late onset schizophrenia risk in the UK Biobank: A prospective exposure-wide association study, BMJ Mental Health (PDF).
3. Markchom, Liang, H., and Ferryman, J. (2025) Review of Explainable Graph-Based Recommender Systems, ACM Computing Surveys.
4. Rina Su, Neil Boonham, Huizhi Liang, Ankush Prashar. (2025) Weed Detection Using Spectral Imaging across Diverse Environments: Identifying Optimal Weeding Times. Smart Agricultural Technology (PDF).
5. Judith Rose Harrison, Song Ling Tang, Bede Burston, Alexander Robertson, Huizhi Liang, John Paul Taylor. (2025) Large Language Models: A Paradigm Shift for Dementia Diagnosis and Care. British Journal of Hospital Medicine.
6. Zhu T, Duan S, Liang H, Li F, Zhang W. (2025) Multiangle correlation feature extraction and disease prediction model construction for patients with post-stroke dysarthria. IEEE Transactions on Neural Systems and Rehabilitation Engineering.
7. Zhang H, Wang D, Sun Z, Li Y, Sun Y, Liang H, Wang W. (2025) KG4RecEval: Does Knowledge Graph Really Matter for Recommender Systems? ACM Transactions on Information Systems.
8. Haifeng Li, Xueying Zhang, Shufei Duan, Huizhi Liang (2024) Speech Emotion Recognition Based on Bi-directional Acoustic-Articulatory Conversion. Knowledge-Based Systems.
9. Markchom, T., Liang, H., and Ferryman, J. (2023) Explainable Meta-Path Based Recommender Systems. IEEE Transaction on Recommender Systems. Accepted.
10. Li Liangqi，ZHANG Xueying，DUAN Shufei，XIAO Zhongzhe，JIA Hairong，Huizhi Liang (2023) Construction and Evaluation of Mandarin Multimodal emotional speech Database. Journal of Fudan University (Natural Science). Chinese. Accepted
11. Li Hai-feng，Zhang Xue-ying，Duan Shu-fei，Jia Hai-rong，Huizhi Liang (2023) Fusing Bi-MGAN and ResTCN-FDA for Mandarin emotion recognition. Journal of Zhejiang University (Engineering Science). Chinese. Accepted
12. Markchom, T., Liang, H., and Ferryman, J. (2023) Scalable and Explainable Visually-Aware Recommender Systems. Knowledge-Based Systems. (PDF) G1, G2
13. Liang, H. and Markchom, T. (2022) TNE: A General Time-aware Network Representation Learning Framework for Temporal Applications. Knowledge-Based Systems. (PDF)  G1
14. Liang, H. (2020) DRprofiling: Deep Reinforcement User Profiling for Recommendations in Heterogenous Information Networks. IEEE TKDE. (PDF) G1
15. Liang, H., Ganeshbabu, G., Thorne, T. (2020). A Dynamic Bayesian Network Approach for Analysing Topic-sentiment Evolution. IEEE ACCESS. (PDF|IEEE) G3
16. Wang, Q., Cui, M., & Liang, H. (2016). Semantic-Aware Blocking for Entity Resolution. IEEE TKDE 2016 28(1): 166-180. ( PDF | IEEE) G2
17. Ramadan, B., Christen, P., Liang, H., Gayler, R. W. (2015). Dynamic Sorted Neighborhood Indexing for Real-Time Entity Resolution. JDIQ 2015, 6(4):15:1-15:29. (PDF | ACM) G2
18. Liang, H., Xu, Y., Li, Y., & Nayak, R. (2012). Personalized Recommender Systems Integrating Social tags and Item Taxonomy. WIAS 2012. Vol.10, No.3, 227-289. (PDF) G1

• Conference Papers

1. Jack Westmoreland, Huizhi Liang (2025). SuSEF: Summarized Section Embedding with Fusion for Scientific Paper Recommendation. RAAI 2025
2. Varun Khurana, Cheng Siong Chin and Huizhi Liang (2025). Imagining the Rare: Diffusion-Augmented and Few-Shot Learning Approaches for Severely Imbalanced Mushroom Species Classification. RAAI 2025
3. Pengzhen Xie and Huizhi Liang (2025). Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation. RAAI 2025
4. Jiaying Hong, Ting Zhu, Thanet Markchom and Huizhi Liang (2025). Art2Music: Generating Music for Art Images with Multi-modal Feeling Alignment. RAAI 2025
5. MTLM: Incorporating Bidirectional Text Information to Enhance Language Model Training in Speech Recognition Systems. ECC 2025
6. Manish Bhardwaj, Huizhi Liang, Ashwin Sivaharan, Sandip Nandhra, Vaclav Snasel, Tamer El-Sayed, Varun Ojha. Deep Learning–Assisted Detection of Sarcopenia in Cross-Sectional Computed Tomography Imaging. ECC 2025
7. (2025). D2R: Dual Regularization Loss with Collaborative Adversarial Generation for Model Robustness. ICANN 2025
8. Alex Robertson, Huizhi Liang, Judith Harrison (2025). MemoryChat: Leveraging Large Language Models as Conversational Agents to Transform the Cognitive Assessment in Dementia Care. LOD 2025
9. Emmanuel Osei-Brefo, Manish Bhardwaj,Huizhi Liang, Yong Zhang, Sharon Scott, Zahid Qayyam (2025). KMagent: A large Language Model based Knowledge Management Platform for Product Innovation. LOD 2025
10. Sreejith Kalathil, Tian Li, Hong Dong, Huizhi Liang (2024). HTEKG: A Human-Trait-Enhanced Literary Knowledge Graph with Language Model Evaluation. KEOD 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (PDF)
11. Zehao Liu, Huizhi Liang (2024) Cross-Metapath based Hashing for Recommendation Systems. LOD 2024 (PDF)
12. Nicolay, Huizhi Liang (2024) Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes. LOD 2024 (PDF)
13. Duaa S. Alqattan, Rui Sun, Huizhi Liang, Vaclav Snasel, Guiseppe Nicosia, Rajiv Ranjan, Varun Ojha (2024). Security Assessment of Hierarchical Federated Deep Learning. ICANN 2024
14. Huizhi Liang, Zhiling Zhou, Zhenyu Hou, Chris Ryder, Rodney Jones. HCU: A Multi-lingual Health Claim Dataset and its NLP Applications. In IBICA 2023
15. Ashwin Kumar Uniyal,Huizhi Liang, Varun Ojha, Self-supervised learning for Pathological Speech Analysis of Parkinson’s Disease. In IBICA 2023
16. Harry Peach, Nicolay Rusnachenko, Mayank Baraskar, and Huizhi Liang, Using Sentence Embedding Techniques for Enhancing Terms-of-Service Text Summarization. In IBICA 2023
17. Junzhe Zhao, Huizhi Liang, Nicolay Rusnachenko, Dialogue Agents with Literary Character Personality Traits. WI-IAT 2023 (IEEE | PDF)
18. Jamie Morris, Zehao Liu, Huizhi Liang, Sidhartha Nagala, Xia Hong, ThyExp: An explainable AI-assisted Decision Making Toolkit for Thyroid Nodule Diagnosis based on Ultra-sound Images. CIKM 2023 (ACM | PDF)
19. Wang, Y., Liang, H., Zhai, B. (2023) Temporal Neighborhood based Self-supervised Pre-training Model for Sleep Stages Classification. ICBBT 2023 Accepted (ACM | PDF)
20. Li, X., Liang, H., Ryder, C., Jones, R., Liu, Z. (2022) Attractiveness Analysis for Health claims on Food Packages. AusDM 2022 (Springer | PDF) 
21. Liang, H., Liu, Z., Markchom, T. (2022) Relation-aware Blocking for Scalable Recommendation Systems. CIKM 2022 (ACM | PDF) G1 G2
22. Li, X., Liang, H. and Nagala, S., Chen, J. (2022) Improving Ultrasound Image Classification With Local Texture Quantisation. ICASSP 2022 (IEEE | PDF | Video)
23. Li, X., Liang, H. and Liu, Z. (2021) Health Claims Unpacked: A toolkit to Enhance the Communication of Health Claims for food. CIKM 2021 (ACM | PDF | Video) G3
24. Markchom, T. and Liang, H. (2021) Augmenting visual information in knowledge graphs for recommendations. In: ACM IUI. (PDF | Video) G1
25. Xu, Z., Wu, J., Xia, Q., Pan, Z., Ren, J. and Liang, H. (2020). Identity-aware attribute recognition via real-time distributed inference in mobile edge clouds. ACM multi-media. (PDF | video) 
26. Wang, Q., Cui, M., & Liang, H. (2016). Semantic-aware blocking for entity resolution. ICDE 2016: 1468-1469.  (PDF | IEEE) G2
27. Liang, H. & Baldwin T. (2015). A Probabilistic Rating Auto-encoder for Personalized Recommender Systems. CIKM 2015: 1863-1866. (PDF | ACM | Poster) G1G2
28. Liang, H., Wang Y., Christen P., & Gayler, R. W. (2014). Noise-Tolerant Approximate Blocking for Dynamic Real-Time Entity Resolution. PAKDD 2014: 449-460. (PDF | Springer) G2
29. Ramadan, B., Christen, P., Liang, H. (2014). Dynamic Sorted Neighborhood Indexing for Real-Time Entity Resolution. ADC 2014: 1-12. (PDF | Springer) G2
30. Liang, H., Du, H., & Wang, Q. (2014). Real-time Collaborative Filtering Recommender Systems. AusDM 2014. (PDF | slides) G1 G2
31. Li, S., Liang, H., and Ramadan, B. (2013). Two Stage Similarity-aware Indexing for Large-scale Real-time Entity Resolution. AusDM 2013. (PDF) G2
32. Liang, H., Xu, Y., Tjondronegoro, D., & Christen, P. (2012). Time-aware Topic Recommendation Based on Micro-blogs. CIKM 2015: 1657-1661. (PDF | ACM) G1
33. Liang, H., Xu, Y., Li, Y., & Nayak, R. (2010). Personalized Recommender System Based on Item Taxonomy and Folksonomy. CIKM 2010: 1641-1644. (PDF | ACM) G1
34. Liang, H., Xu, Y.,  Li, Y., & Nayak, R. (2010). Connecting Users and Items with Weighted Tags for Personalized Item Recommendations. HT 2010: 51-60. (PDF | ACM) G1
35. Bhuiyan, T., Xu, Y., Jøsang, A., & Liang, H. (2010). Developing Trust Networks Based on User Tagging Information for Recommendation Making. WISE 2010: 357-364. (PDF | Springer) G1
36. Liang, H., Xu, Y.,  Li, Y., Nayak, R., & Weng, L. (2009). Personalized Recommender Systems Integrating Social tags and Item Taxonomy. WI 2009: 540-547. (PDF | ACM) G1
37. Liang, H., Xu, Y., Li, Y., & Nayak, R. (2009). Collaborative Filtering Recommender Systems based on Popular Tags. ADCS 2009: 3-10. (PDF) G1
38. Liang, H., Xu, Y., Li, Y., & Nayak, R. (2009). Tag Based Collaborative Filtering for Recommender Systems. RSKT 2009: 666-673. (PDF | Springer) G1

• Workshop Papers

1. Tian Li, Yujian Sun, Huizhi Liang. Chinchunmei at SemEval-2025 Task 11: Boosting the Large Language Model’s Capability of Emotion Perception using Contrastive Learning
2. Ting Zhu, Liting Huang, Huizhi Liang. tinaal at SemEval-2025 Task 11: Enhancing Perceived Emotion Intensity Prediction with Boosting Fine-Tuned Transformers
3. Kun Lu, Huizhi Liang. NCL-NLP at SemEval-2025 Task 11: Using Prompting engineering framework and Low Rank Adaptation of Large Language Models for Multi-label Emotion Detection
4. Shu Li,  George Snape, Huizhi Liang. NCLTeam at SemEval-2025 Task 10: Enhancing Multilingual, multi-class, and Multi-Label Document Classification via Contrastive Learning Augmented Cascaded UNet and Embedding based Approaches
5. Emmanuel Osei-Brefo, Huizhi Liang.  OseiBrefo-Liang at SemEval-2025 Task 8: A Multi-Agent LLM code generation approach for answering Tabular Questions
6. Alex Robertson, Huizhi Liang. NCL-AR at SemEval-2025 Task 7: A Sieve Filtering Approach to Refute the Misinformation within Harmful Social Media Posts
7. Jiaying Hong, Thanet Markchom, Jianfei Xu, Tong Wu, Huizhi Liang. NCL-UoR at SemEval-2025 Task 3: Detecting Multilingual Hallucination and Related Observable Overgeneration Text Spans with Modified RefChecker and Modified SeflCheckGPT. SemEval-2025
8. Thanet Markchom, Tong Wu, Liting Huang, Huizhi Liang. UoR-NCL at SemEval-2025 Task 1: Using Generative LLMs and CLIP Models for Multilingual Multimodal Idiomaticity Representation. SemEval-2025
9. Emmanuel Osei-Brefo, Huizhi Liang. NU @ WASSA2024: Enhancing Personality Predictions with Knowledge Graphs Using Graphical Neural Networks and LightGBM as Ensemble Model. WASSA 2024, accepted
10. Tian Li, Nicolay Rusnachenko, Huizhi Liang. Chinchunmei at WASSA 2024 Empathy and Personality Shared Task: Boosting LLM’s Prediction with Role-play Augmentation and Contrastive Reasoning Calibration. WASSA 2024, accepted
11. Liting Huang, Huizhi Liang. Zhenmei at WASSA-2024 Empathy and Personality Shared Track 2: Incorporating Pearson Correlation Coefficient as a Regularization Term for Enhanced Empathy and Emotion Prediction in Conversational Turns. WASSA 2024, accepted
12. Huiyu Yang, Liting Huang, Tian Li, Nicolay Rusnachenko. hyy33 at WASSA 2024 Empathy and Personality Shared Task: Using the CombinedLoss and FGM for Enhancing BERT-based Models in Emotion and Empathy Prediction from Conversation Turns. WASSA 2024, accepted
13. Junzhe Zhao, Yingxi Wang, Huizhi Liang, Nicolay Rusnachenko, NCL_NLP at SemEval-2024 Task 7: CoT-NumHG: A CoT-Based SFT Training Strategy with Large Language Models for Number-Focused Headline Generation. SemEval-2024. Ranked the 2nd out of 16 teams
14. Nicolay Rusnachenko, Huizhi Liang. nicolay-r at SemEval-2024 Task 3: Using Flan-T5 for Reasoning Emotion Cause in Conversations with Chain-of-Thoughts on Emotion States. SemEval-2024. Ranked the 3rd out of 14 teams.
15. Thanet Markchom, Subin Jung, Huizhi Liang, NU-RU at SemEval-2024 Task 6: Hallucination and Related Observable Overgeneration Mistake Detection Using Hypothesis-Target Similarity and SelfCheckGPT. SemEval-2024
16. Feng Xiong, Thanet Markchom, Ziwei Zheng, Subin Jung, Varun Ojha, Huizhi Liang, NCL–UoR at SemEval-2024 Task 8: Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection. SemEval-2024
17. Markchom, T., Liang, H., Gitau, J., Liu, Z., Ojha, V., Taylor, L., Bonnici, J., and Alshadadi, A. (2023) UoR-NCL at SemEval-2023 Task 1: Learning Word-Sense and Image Embeddings for Word Sense Disambiguation. In: SemEval-2023. (PDF)
18. Rusnachenko, N., Markchom, T., and Liang, H. (2023) nclu_team at SemEval-2023 Task 6C1 and 6C2: Attention-based Approaches for Large Court Judgement Prediction with Explanation. In: SemEval-2023. (PDF) Ranked the 3rd of Task 6C2.
19. Zhao, J., Wang, Y., Rusnachenko, N., and Liang, H., Legal_try at SemEval-2023 Task 6: Voting Heterogeneous Models for Entities identification in Legal Documents. In SemEval-2023. (PDF)
20. Pugazhenthi T., Liang, H. (2022) Improving conversational recommender systems via knowledge graph-based semantic fusion with historical interaction data. In: 2022 IEEE International Conference on Big Data Workshop. (PDF)
21. Markchom, T., Liang, H., and Chen, J. (2022) UoR-NCL at SemEval-2022 Task 3: Fine-Tuning the BERT-Based Models for Validating Taxonomic Relations. In: SemEval-2022. (PDF)
22. Osei-Brefo, E., and Liang, H. (2022). UoR-NCL at SemEval-2022 Task 6: Using ensemble loss with {BERT} for detecting intended sarcasm. In: SemEval-2022. (PDF)
23. Liu, Z., Haines, C. and Liang, H. (2021) UoR at SemEval-2021 task 7: utilizing pre-trained DistilBert model and multi-scale CNN for humor detection. In: SemEval-2021. (PDF)
24. Markchom, T. and Liang, H. (2021) UoR at SemEval-2021 task 4: using pre-trained BERT Token embeddings for question answering of abstract meaning. In: SemEval-2021. (PDF)
25. Osei-Brefo, E., Markchom, T. and Liang, H. (2021) UoR at SemEval-2021 task 12: on crowd annotations: learning with disagreements to optimise crowd truth. In: SemEval-2021. (PDF)
26. Zehao Liu, Emmanuel Osei-Brefo, Siyuan Chen, Huizhi Liang (2020). UoR at SemEval-2020 Task 8: Gaussian Mixture Modelling (GMM) Based Sampling Approach for Multi-modal Memotion Analysis. SemEval-2020. (PDF) 
27. Thanet Markchom, Bhuvana Dhruva, Chandresh Pravin, Huizhi Liang. (2020) UoR at SemEval-2020 Task 4: Pre-trained Sentence Transformer Models for Commonsense Validation and Explanation. SemEval-2020. (PDF)
28. Chiara Zucco, Huizhi Liang, Giuseppe Di Fatta, Mario Cannataro. (2018): Explainable Sentiment Analysis with Applications in Medicine. BIBM 2018: 1740-1747 G3
29. Fukuda, T., Nishimura, S., Liang, H. (2016) Towards Sentiment Analysis in Elderly Care Facility. JSAI-isAI Workshops 2016: 143-154. (Springer) G3
30. Liang, Z., Liang, H., Nishimura, T., Martell, M. (2016) Quantitative Analysis of Difference between Good and Bad Motion During Coordinated Movements and Its Potential Application to Healthy Ageing. (HAT-MASH 2016, Oral Presentation) G3
31. Xu, S., Liang, H., & Baldwin, T. (2016). UNIMELB at SemEval-2016 Tasks 4A and 4B: An Ensemble of Neural Networks and a Word2Vec Based Model for Sentiment Classification. SemEval@NAACL-HLT 2016: 183-189. Ranked the 3rd out of 34 teams world wide. (PDF) G3
32. Hoogeveen, D., Li, Y., Liang, H., Salehi, B., Baldwin, T., Duong, Long. (2016). UniMelb at SemEval-2016 Task 3: Identifying Similar Questions by combining a CNN with String Similarity Measures. SemEval@NAACL-HLT 2016: 851-856. (PDF) G3
33. Liang, H., Fothergill, R., & Baldwin T. (2015). RoseMerry: A Baseline Message-level Sentiment Classification System, SemEval@NAACL-HLT 2015: 551-555. (PDF | ACLWEB) G3
34. Ramadan, B., Christen, P., Liang, H., Gayler, R. W., Hawking, D. (2013). Dynamic Similarity-Aware Inverted Indexing for Real-Time Entity Resolution. PAKDD Workshops, 2013: 47-58. (PDF | Springer) G2
35. Liang, H., Hogan, J., Xu, Y. (2010). Parallel User profiling based on Folksonomy for Large Scaled Recommender Systems-An implementation of Cascading MapReduce. ICDM 2010 workshop: 154-161. (PDF | IEEE) G2
36. Liang, H., Xu, Y., & Li, Y. (2010). Mining Users’ Opinions based on Item Folksonomy and Taxonomy for Personalized Recommender Systems. ICDM 2010 workshop: 1128-1135. (PDF | IEEE) G1
37. Liang, H., Xu, Y., Li, Y., & Nayak, R., Shaw, G. (2010). A Hybrid Recommender System based on Weighted Tags. SDM 2010 workshop. (PDF) G1
38. Liang, H., Xu, Y., Li, Y., & Nayak, R. (2008). Collaborative Filtering Recommender Systems Using Tag Information. WI 2008: 59-62. (PDF | ACM) G1

• Thesis

Huizhi Liang, PhD Thesis, User Profiling Based on Folksonomy Information in Web 2.0 for Personalized Recommendations (2011) (PDF)