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Finding Questions in Medical Forum Posts Using Sequence Labeling Approach

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Computational Linguistics and Intelligent Text Processing (CICLing 2018)

Abstract

Complex medical question answering system in medical domain receives a question in form of long text that need to be decomposed before further processing. This research propose sequence labeling approach to decompose that complex question. Two main tasks in segmenting complex question sentence are detecting sentence boundary with its type, and recognizing word that could be ignored in sentence. The proposed sequence labeling method achieves F1 score of 0.83 in detecting beginning sentence boundary and 0.93 when determining sentence type. When recognizing the word sequence that could be ignored in sentence, the sequence labeling method achieves F1 score of 0.90.

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Notes

  1. 1.

    https://www.healthboards.com/.

  2. 2.

    http://www.nlm.nih.gov/research/umls/.

  3. 3.

    https://github.com/famrashel/idn-tagged-corpus.

  4. 4.

    https://health.detik.com/.

  5. 5.

    http://pd.fk.ub.ac.id/wp-content/uploads/2014/12/SKDI-disahkan.pdf.

References

  1. Dinakaramani, A., Rashel, F., Luthfi, A., Manurung, R.: Designing an Indonesian part of speech tagset and manually tagged indonesian corpus. In: 2014 International Conference on Asian Language Processing (IALP), pp. 66–69, October 2014. https://doi.org/10.1109/IALP.2014.6973519

  2. Evang, K., Basile, V., Chrupała, G., Bos, J.: Elephant: sequence labeling for word and sentence segmentation. In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1422–1426, Seattle, Washington, USA, October 2013. Association for Computational Linguistics. http://www.aclweb.org/anthology/D13-1146

  3. Hakim, A.N., Mahendra, R., Adriani, M., Ekakristi, A.S.: Corpus development for Indonesian consumer-health question answering system. In: 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS) (2017)

    Google Scholar 

  4. Mahendra, R., Hakim, A.N., Adriani, M.: Towards question identification from online healthcare consultation forum post in bahasa. In: 2017 International Conference on Asian Language Processing (IALP) (2017)

    Google Scholar 

  5. Roberts, K., Masterton, K., Fiszman, M., Kilicoglu, H., Demner-fushman, D.: Annotating question decomposition on complex medical questions. In: Proceedings of LREC (2014)

    Google Scholar 

  6. Roberts, K., Fiszman, M., Kilicoglu, H., Demmer-Fushman, D.: Decomposing consumer health questions. In: Proceedings of the 2014 Workshop on Biomedical Natural Languange Processing, pp. 29–37. U.S. National Library of Medicine (2017)

    Google Scholar 

  7. Saputra, I.F., Mahendra, R., Wicaksono, A.F.: Keyphrases extraction from user-generated contents in healthcare domain using long short-term memory networks. In: Proceedings of the BioNLP 2018 workshop, pp. 28–34, Melbourne, Australia, July 2018. Association for Computational Linguistics. https://doi.org/10.18653/v1/W18-2304. https://aclanthology.org/W18-2304

  8. Sondhi, P., Gupta, M., Zhai, C., Hockenmaier, J.: Shallow information extraction from medical forum data. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, COLING 2010, pp. 1158–1166. Association for Computational Linguistics, Stroudsburg (2010). http://dl.acm.org/citation.cfm?id=1944566.1944699

  9. Wicaksono, A.F., Vania, C., Distiawan, B., Adriani, M.: Automatically building a corpus for sentiment analysis on Indonesian tweets. In Proceedings of the 28th Pacific Asia Conference on Language, Information and Computation, PACLIC 28, Cape Panwa Hotel, Phuket, Thailand, December 12–14 (2014), pp. 185–194 (2014). http://aclweb.org/anthology/Y/Y14/Y14-1024.pdf

  10. Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735–1780 (1997). MIT Press

    Google Scholar 

  11. Devlin, J., Chang, M.-W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1 (Long and Short Papers), pp. 4171–4186. Association for Computational Linguistics, Minneapolis (2019)

    Google Scholar 

  12. Wilie, B., et al.: IndoNLU: benchmark and resources for evaluating Indonesian natural language understanding. In: Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pp. 843–857. Association for Computational Linguistics, Suzhou (2020)

    Google Scholar 

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Correspondence to Rahmad Mahendra .

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Ekakristi, A.S., Mahendra, R., Adriani, M. (2023). Finding Questions in Medical Forum Posts Using Sequence Labeling Approach. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2018. Lecture Notes in Computer Science, vol 13396. Springer, Cham. https://doi.org/10.1007/978-3-031-23793-5_6

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  • DOI: https://doi.org/10.1007/978-3-031-23793-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23792-8

  • Online ISBN: 978-3-031-23793-5

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