Article

Liang, H. (2022) DRprofiling: deep reinforcement user profiling for recommendations in heterogenous information networks. Transactions on Knowledge and Data Engineering, 34 (4). pp. 1723-1734. ISSN 1558-2191 doi: https://doi.org/10.1109/TKDE.2020.2998695

Liang, H. and Markchom, T. (2022) TNE: a general time-aware network representation learning framework for temporal applications. Knowledge-Based Systems, 240. 108050. ISSN 0950-7051 doi: https://doi.org/10.1016/j.knosys.2021.108050

Liang, H., Ganeshbabu, U. and Thorne, T. (2020) A dynamic Bayesian network approach for analysing topic-sentiment evolution. IEEE Access, 8. 54164 -54174. ISSN 2169-3536 doi: https://doi.org/10.1109/ACCESS.2020.2979012

Ramadan, B., Christen, P., Liang, H. and Gayler, R. W. (2015) Dynamic sorted neighborhood indexing for real-time entity resolution. Journal of Data and Information Quality, 6 (4). 15. ISSN 1936-1955 doi: https://doi.org/10.1145/2816821

Wang, Q., Cui, M. and Liang, H. (2015) Semantic-aware blocking for entity resolution. IEEE Transactions on Knowledge and Data Engineering, 28 (1). pp. 166-180. ISSN 1558-2191 doi: https://doi.org/10.1109/TKDE.2015.2468711

Conference or Workshop Item

Morris, J., Liu, Z., Liang, H., Nagala, S. and Hong, X. ORCID: https://orcid.org/0000-0002-6832-2298 (2023) ThyExp: an explainable AI-assisted decision making toolkit for thyroid nodule diagnosis based on ultra-sound images. In: 32nd ACM International Conference on Information and Knowledge Management, Saturday 21 - Wednesday 25 October 2023, Birmingham,UK, pp. 5371-5375. doi: https://doi.org/10.1145/3583780.3615131

Li, X., Liang, H., Nagala, S. and Chen, J. (2022) Improving ultrasound image classification with local texture quantisation. In: The International Conference on Acoustics, Speech, & Signal Processing (ICASSP). doi: https://doi.org/10.1109/ICASSP43922.2022.9747883

Li, X., Liang, H. and Liu, Z. (2021) Health claims unpacked: a toolkit to enhance the communication of health claims for food. In: The Conference on Information and Knowledge Management (CIKM), 1-5 NOV 2021, Gold Coast, Queensland, Australia, pp. 4744-4748. doi: https://doi.org/10.1145/3459637.3481984 (CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management)

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, 5-6 August 2021, Bangkok.

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, 5-6 August 2021, Bangkok.

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, 5-6 August 2021, Bangkok.

Markchom, T. and Liang, H. (2021) Augmenting visual information in knowledge graphs for recommendations. In: ACM International Conference on Intelligent User Interfaces, 13-17 April 2021, Texas. doi: https://doi.org/10.1145/3397481.3450686

Zichuan, X., Jiangkai, W., Qiufen, X., Pan, Z., Jiankang, R. and Liang, H. (2020) Identity-aware attribute recognition via real-time distributed inference in mobile edge clouds. In: ACM multi-media, 12-16 Oct 2020, Seattle, United States, pp. 3265-3273. doi: https://doi.org/10.1145/3394171.3414048

Markchom, T., Dhruva, B., Pravin, C. and Liang, H. (2020) UoR at SemEval-2020 task 4: pre-trained sentence transformer models for commonsense validation and explanation. In: International Workshop on Semantic Evaluation 2020, December 12-13, 2020, Barcelona, Spain, pp. 430-436.

Liu, Z., Osei-Brefo, E., Chen, S. and Liang, H. (2020) UoR at SemEval-2020 task 8: Gaussian mixture modelling (GMM) based sampling approach for multi-modal memotion analysis. In: International Workshop on Semantic Evaluation 2020, December 12-13, 2020, Barcelona, Spain, pp. 1201-1207.

Liang, H. and Baldwin, T. (2015) A probabilistic rating auto-encoder for personalized recommender systems. In: Conference on Information and Knowledge Management, 19-23 October, Melbourne, Australia.

Liang, H., Wang, Y., Christen, P. and Gayler, R. (2014) Noise-tolerant approximate blocking for dynamic real-time entity resolution. In: The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 13-16 May 2014, Taiwan, pp. 449-460.