Natural language processing for analysis of systematic reviews

Project Member(s): Piccardi, M.

Funding or Partner Organisation: Capital Markets Cooperative Research Centre - Capital Markets CRC (Capital Markets - CRC Scholarship (External))

Start year: 2015

Summary: Natural language processing for analysis of systematic reviews

Publications:

Poostchi, H & Piccardi, M 2022, 'BiLSTM-SSVM: Training the BiLSTM with a Structured Hinge Loss for Named-Entity Recognition', IEEE Transactions on Big Data, vol. 8, no. 1, pp. 203-212.
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Poostchi, H, Borzeshi, EZ & Piccardi, M 1970, 'BILSTM-CRF for Persian named-entity recognition armanpersonercorpus: The first entity-annotated Persian dataset', LREC 2018 - 11th International Conference on Language Resources and Evaluation, Language Resources and Evaluation Conference, European Language Resources Association (ELRA, Miyazaki, Japan, pp. 4427-4431.

Poostchimohammadabadi, H & Piccardi, M 1970, 'A multi-constraint structured hinge loss for named-entity recognition', Proceedings of The 17th Annual Workshop of the Australasian Language Technology Association, Annual Workshop of the Australasian Language Technology Association, ACLWEB, Sydney, NSW, Australia, pp. 41-46.

Poostchi, H & Piccardi, M 1970, 'Cluster Labeling by Word Embeddings and WordNet’s Hypernymy', https://www.aclweb.org/anthology/U18-1, Annual Workshop of The Australasian Language Technology Association, Dunedin, New Zealand.

Poostchi, H, Borzeshi, EZ, Abdous, M & Piccardi, M 1970, 'PersoNER: Persian named-entity recognition', COLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016: Technical Papers, International Conference on Computational Linguistics, COLING, Osaka, Japan, pp. 3381-3389.

Keywords: machine learning, health informatics, low-value care

FOR Codes: Health not elsewhere classified, Pattern Recognition and Data Mining, Computer Software and Services not elsewhere classified, Natural language processing, Other health not elsewhere classified, Information systems, technologies and services not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.