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Dr Huizhi Liang

Email:
huizhi.liang@reading.ac.uk
Phone:
+44 (0) 118 378 8757
Job title:
Lecturer in Computer Science

Office

Room 149

Building location

Polly Vacher

Areas of interest

Data mining
Machine learning
Recommender systems
Personalisation.

Background

Before joining the University of Reading, Dr Huizhi worked as a research fellow at LIP6, Pierre et Marie Curie University and French National Center for Scientific Research (CNRS), Department of Computing and Information Systems at the University of Melbourne, and Research School of Computer Science at the Australian National University.

Websites/blogs

See her personal website for more information. You can also find her on Google Scholar.

Publications

Li, X. , Liang, H. , Liu, Z. (2021) Health claims unpacked: a toolkit to enhance the communication of health claims for food.
Liu, Z. , Haines, C. , Liang, H. (2021) UoR at SemEval-2021 task 7: utilizing pre-trained DistilBert model and multi-scale CNN for humor detection.
Osei-Brefo, E. , Markchom, T. , Liang, H. (2021) UoR at SemEval-2021 task 12: on crowd annotations: learning with disagreements to optimise crowd truth. SemEval-2021
Markchom, T. and Liang, H. (2021) UoR at SemEval-2021 task 4: using pre-trained BERT Token embeddings for question answering of abstract meaning.
Markchom, T. and Liang, H. (2021) Augmenting visual information in knowledge graphs for recommendations. | doi: http://dx.doi.org/10.1145/3397481.3450686

Liu, Z. , Osei-Brefo, E. , Chen, S. , Liang, H. (2020) UoR at SemEval-2020 task 8: Gaussian mixture modelling (GMM) based sampling approach for multi-modal memotion analysis. pp. 1201-1207.
Markchom, T. , Dhruva, B. , Pravin, C. , Liang, H. (2020) UoR at SemEval-2020 task 4: pre-trained sentence transformer models for commonsense validation and explanation. pp. 430-436.
Zichuan, X. , Jiangkai, W. , Qiufen, X. , Pan, Z. , Jiankang, R. , Liang, H. (2020) Identity-aware attribute recognition via real-time distributed inference in mobile edge clouds. ACM multi-media pp. 3265-3273. | doi: http://dx.doi.org/10.1145/3394171.3414048
Liang, H. (2020) DRprofiling: deep reinforcement user profiling for recommendations in heterogenous information networks. Transactions on Knowledge and Data Engineering ISSN: 1558-2191 | doi: http://dx.doi.org/10.1109/TKDE.2020.2998695
Liang, H. , Ganeshbabu, U. , Thorne, T. (2020) A dynamic Bayesian network approach for analysing topic-sentiment evolution. IEEE Access , 8 pp. 54164 -54174. ISSN: 2169-3536 | doi: http://dx.doi.org/10.1109/ACCESS.2020.2979012

Liang, H. and Baldwin, T. (2015) A probabilistic rating auto-encoder for personalized recommender systems.
Ramadan, B. , Christen, P. , Liang, H. , Gayler, R. (2015) Dynamic sorted neighborhood indexing for real-time entity resolution. Journal of Data and Information Quality , 6 (4). ISSN: 1936-1955 | doi: http://dx.doi.org/10.1145/2816821
Wang, Q. , Cui, M. , 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: http://dx.doi.org/10.1109/TKDE.2015.2468711

Liang, H. , Wang, Y. , Christen, P. , Gayler, R. (2014) Noise-tolerant approximate blocking for dynamic real-time entity resolution. pp. 449-460.