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Number of items: 9.


Dong, Hang ORCID: 0000-0001-6828-6891, Wang, Wei, Huang, Kaizhu and Coenen, Frans ORCID: 0000-0003-1026-6649
(2021) Automated Social Text Annotation With Joint Multilabel Attention Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 32 (5). pp. 2224-2238.


Dong, Hang ORCID: 0000-0001-6828-6891, Wang, Wei, Huang, Kaizhu and Coenen, Frans ORCID: 0000-0003-1026-6649
(2019) Joint Multi-Label Attention Networks for Social Text Annotation. In: 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2019-6-2 - 2019-6-7, Minneapolis, USA.


Dong, Hang ORCID: 0000-0001-6828-6891, Wang, Wei, Coenen, Frans ORCID: 0000-0003-1026-6649 and Huang, Kaizhu
(2020) Knowledge Base Enrichment by Relation Learning from Social Tagging Data. Information Sciences, 526. pp. 203-220.


Chen, Jiaoyan, Dong, Hang, Hastings, Janna, Jiménez-Ruiz, Ernesto, López, Vanessa, Monnin, Pierre, Pesquita, Catia, Skoda, Petr and Tamma, Valentina AM ORCID: 0000-0002-1320-610X
(2023) Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities. TGDK, 1 (1). 5:1-5:1.


Dong, Hang ORCID: 0000-0001-6828-6891, Wang, Wei and Coenen, Frans ORCID: 0000-0003-1026-6649
(2018) Learning Relations from Social Tagging Data. .


Dong, Hang ORCID: 0000-0001-6828-6891, Wang, Wei and Liang, Hai-Ning
(2015) Learning Structured Knowledge from Social Tagging Data A critical review of methods and techniques. In: 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity), 2015-12-19 - 2015-12-21.


Dong, Hang ORCID: 0000-0001-6828-6891
(2020) Learning and Leveraging Structured Knowledge from User-Generated Social Media Data. PhD thesis, University of Liverpool.


Dong, Hang ORCID: 0000-0001-6828-6891, Wang, Wei and Coenen, Frans ORCID: 0000-0003-1026-6649
(2018) Rules for Inducing Hierarchies from Social Tagging Data. .


Chen, Yuyun, Dong, Hang ORCID: 0000-0001-6828-6891 and Wang, Wei
(2018) Topic-graph based recommendation on social tagging systems. In: DSIT2018: 2018 International Conference on Data Science and Information Technology.

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