@inproceedings{32010791d58246aa97bdfbd670c60fbd,
title = "Finding Questions in Medical Forum Posts Using Sequence Labeling Approach",
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.",
keywords = "Chunking, Medical question answering, Question decomposition, Sequence labeling",
author = "Ekakristi, \{Adrianus Saga\} and Rahmad Mahendra and Mirna Adriani",
note = "Publisher Copyright: {\textcopyright} 2023, Springer Nature Switzerland AG.; 19th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2018 ; Conference date: 18-03-2018 Through 24-03-2018",
year = "2023",
doi = "10.1007/978-3-031-23793-5\_6",
language = "English",
isbn = "9783031237928",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "62--73",
editor = "Alexander Gelbukh",
booktitle = "Computational Linguistics and Intelligent Text Processing - 19th International Conference, CICLing 2018, Revised Selected Papers",
address = "Germany",
}