Xingyi Song

Journal articles

• Chilman N, Song X, Roberts A, Tolani E, Stewart R, Chui Z, Birnie K, Harber-Aschan L, Gazard B, Chandran D , Sanyal J et al (2021) Text mining occupations from the mental health electronic health record: A natural language processing approach using records from the Clinical Record Interactive Search (CRIS) platform in south London, UK. BMJ Open, 11(3).
• Maynard D, Lepori B, Petrak J, Song X & Laredo P (2020) Using ontologies to map between research data and policymakers’ presumptions: the experience of the KNOWMAK project. Scientometrics. View this article in WRRO
• He L, Gilbert M & Song X (2019) A Python script for adaptive layout optimization of trusses. Structural and Multidisciplinary Optimization. View this article in WRRO
• Jackson R, Kartoglu I, Stringer C, Gorrell G, Roberts A, Song X, Wu H, Agrawal A, Lui K, Groza T , Lewsley D et al (2018) CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital. BMC Medical Informatics and Decision Making, 18. View this article in WRRO
• Song X, Petrak J, Jiang Y, Singh I, Maynard D & Bontcheva K () Classification aware neural topic model for COVID-19 disinformation categorisation. PLOS ONE, 16(2), e0247086-e0247086.

Conference proceedings papers

• Jiang Y, Wang Y, Maynard D & Song X (2020) Comparing topic-aware neural networks for bias detection of news. Proceedings of 24th European Conference on Artificial Intelligence (ECAI 2020), Vol. 325 (pp 2054-2061). Santiago de Compostela, Spain, 29 August 2020 - 2 September 2020. View this article in WRRO
• Song X, Downs J, Velupillai S, Holden R, Kikoler M, Bontcheva K, Dutta R & Roberts A (2020) Using deep neural networks with intra- And inter-sentence context to classify suicidal behaviour. LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp 1303-1310)
• Gao J, Han S, Song X & Ciravegna F (2020) RP-DNN: A tweet level propagation context based deep neural networks for early rumor detection in social media. LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp 6094-6105) View this article in WRRO
• Jiang Y, Petrak J, Song X, Bontcheva K & Maynard D (2019) Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network. Proceedings of the 13th International Workshop on Semantic Evaluation, June 2019 - June 2019.
• Jiang Y, Petrak J, Song X, Bontcheva K & Maynard D (2019) Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network. Proceedings of the 13th International Workshop on Semantic Evaluation. Minneapolis, Minnesota, USA, 6 June 2019 - 7 June 2019. View this article in WRRO
• Song X, Petrak J & Roberts A (2018) A deep neural network sentence level classification method with context information. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (pp 900-904). Brussels, Belgium, 31 October 2018 - 4 November 2018. View this article in WRRO
• Blain F, Song X & Specia L (2016) Sheffield Systems for the English-Romanian WMT Translation Task. Proceedings of the First Conference on Machine Translation
• Song X, Specia L & Cohn T (2014) Data selection for discriminative training in statistical machine translation. Proceedings of the 17th Annual Conference of the European Association for Machine Translation, EAMT 2014 (pp 45-52)
• Song X, Cohn T & Specia L (2013) BLEU deconstructed: Designing a Better MT Evaluation Metric. Proceedings of the 14th International Conference on Intelligent Text Processing and Computational Linguistics (CICLING)
• Song X & Cohn T (2011) Regression and Ranking based Optimisation for Sentence Level Machine Translation Evaluation. Proceedings of the Sixth Workshop on Statistical Machine Translation. Edinburgh, UK

Datasets

• Gao J, Han S & Song X Trained RPDNN LOO-CV models for early rumor detection.