Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts

  1. Benítez-Andrades, José Alberto 4
  2. García-Ordás, María Teresa 1
  3. Russo, Mayra 2
  4. Sakor, Ahmad 2
  5. Fernandes Rotger, Luis Daniel 3
  6. Vidal, Maria-Esther 2
  1. 1 SECOMUCI Research Group, Escuela de Ingenierías Industrial e Informática, Universidad de León,León, Spain
  2. 2 Leibniz University of Hannover and L3S Research Center and TIB Leibniz Information Centre for Science and Technology, Germany
  3. 3 Bakken and Baeck GmbH, Germany
  4. 4 SALBIS Research Group, Department of Electric, Systems and Automatics Engineering, Universidad de León, León, Spain
Revista:
Semantic Web

ISSN: 2210-4968 1570-0844

Año de publicación: 2023

Páginas: 1-20

Tipo: Artículo

DOI: 10.3233/SW-223269 GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Semantic Web

Referencias bibliográficas

  • Abhishek, (2022), International Journal of Computers and Applications, 44, pp. 838, 10.1080/1206212X.2021.1957551
  • Acheampong, (2021), Artificial Intelligence Review, 54, pp. 5789, 10.1007/s10462-021-09958-2
  • 10.1007/978-3-030-55814-7_18
  • S. Arora, Y. Liang and T. Ma, A simple but tough-to-beat baseline for sentence embeddings, in: ICLR, 2017.
  • 10.1145/1526993.1526995
  • Baeza-Yates, (2018), Commun. ACM, 61, pp. 54, 10.1145/3209581
  • 10.5281/zenodo.7101682
  • 10.1109/CBMS52027.2021.00105
  • Budenz, (2020), Journal of Mental Health, 29, pp. 191, 10.1080/09638237.2019.1677878
  • Congosto, (2017), Journal of Network and Computer Applications, 83, pp. 28, 10.1016/j.jnca.2017.01.029
  • Conway, (2016), Current Opinion in Psychology, 9, pp. 77, 10.1016/j.copsyc.2016.01.004
  • 10.1007/978-1-4419-9326-7_5
  • 10.18653/v1/N19-1423
  • 10.1136/bmj.n1787
  • 10.1016/j.cmpb.2021.105968
  • Gaur, (2021), IEEE Internet Computing, 25, pp. 51, 10.1109/MIC.2020.3031769
  • 10.1007/s11920-019-1094-0
  • 10.1155/2022/3604113
  • Gutiérrez, (2021), Communications of the ACM, 64, pp. 96, 10.1145/3418294
  • 10.5888/pcd15.170309
  • 10.2196/35928
  • 10.1109/BigData.2016.7841081
  • L.C. Jain and L.R. Medsker, Recurrent Neural Networks: Design and Applications, 1st edn, CRC Press, Inc., USA, 1999. ISBN: 0849371813.
  • 10.3390/app10175841
  • 10.1002/cpe.7224
  • 10.1109/eScience.2018.00024
  • H. Le, L. Vial, J. Frej, V. Segonne, M. Coavoux, B. Lecouteux, A. Allauzen, B. Crabbé, L. Besacier and D. Schwab, FlauBERT: Unsupervised language model pre-training for French, in: Proceedings of the 12th Language Resources and Evaluation Conference, European Language Resources Association, Marseille, France, 2020, pp. 2479–2490. https://www.aclweb.org/anthology/2020.lrec-1.302.
  • Lehmann, (2015), Semantic Web, 6, pp. 167, 10.3233/SW-140134
  • 10.1145/3532577
  • 10.1007/s13755-020-00128-2
  • 10.3390/app11041838
  • Makita, (2021), Issues in Mental Health Nursing, 42, pp. 437, 10.1080/01612840.2020.1814914
  • Malighetti, (2020), Annual Review of Cybertherapy and Telemedicine, pp. 8
  • 10.1007/978-3-030-00668-6_23
  • L. Martin, B. Muller, P.J.O. Suárez, Y. Dupont, L. Romary, É.V. de la Clergerie, D. Seddah and B. Sagot, CamemBERT: A tasty French language model, in: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020.
  • 10.3389/fpsyg.2022.926709
  • 10.18653/v1/2020.emnlp-demos.2
  • 10.2196/26011
  • 10.3389/fdata.2019.00013
  • 10.1007/978-3-031-06245-2_10
  • 10.1145/3462462.3468881
  • 10.1016/j.asoc.2021.107393
  • Parcheta, (2021), Neural Processing Letters, 53, pp. 3123, 10.1007/s11063-020-10312-w
  • 10.1145/3290605.3300881
  • 10.1007/978-3-030-98305-5
  • P. Ristoski and H. Paulheim, RDF2Vec: RDF graph embeddings for data mining, in: SEMWEB, 2016.
  • Rodriguez-Gonzalez, (2012), Current Bioinformatics, 7, pp. 234, 10.2174/157489312802460721
  • 10.1145/3340531.3412777
  • Santomauro, (2021), The Lancet, 398, pp. 700, 10.1016/S0140-6736(21)02143-7
  • S.D.M.G.- TIB, SDM-RDF2vec, GitHub, 2022.
  • 10.1016/j.psychres.2020.113122
  • Skaik, (2020), ACM Computing Surveys, 53, pp. 129:1, 10.1145/3422824
  • 10.3390/fi13070163
  • 10.2196/24340
  • 10.1007/978-981-13-2514-4_36
  • Turki, (2022), Semantic Web, 14, pp. 233, 10.3233/SW-210444
  • Vallurupalli, (2020), CEUR Workshop Proceedings, 2774, pp. 57
  • 10.2196/17626
  • Vrandecic, (2014), Commun. ACM, 57, pp. 78, 10.1145/2629489
  • 10.7554/eLife.52614
  • 10.3390/cancers11111673
  • 10.1145/3018661.3018706
  • 10.1016/B978-0-12-822201-0.00018-6
  • 10.1109/ISCIPT53667.2021.00164
  • 10.2196/20550
  • 10.3233/FAIA200355
  • 10.1145/3440067.3440077
  • 10.2196/18273
  • Zipfel, (2022), The Lancet Psychiatry, 9, pp. 9, 10.1016/S2215-0366(21)00435-1