Abstract
Chinese chronic disease entity extraction aims to extract health related entities from online questions and answers (QA). Our research tackles challenges in Chinese chronic disease entity extraction from three aspects: Chinese health lexicons construction, feature development, and equivalence conjunctions tagging. We construct large scale Chinese health lexicons based on expert knowledge and the Web resources; develop a feature extraction approach that draws out character, part-of-speech, and lexical features from QA data; and improve the performance of answer entity extraction by leveraging equivalence conjunctions (punctuation marks and conjunctional words) in Chinese to capture dependencies between tags of entities. Experiments on question and answer entity extraction demonstrate that the Precision, Recall and F-1 score are improved using our proposed features, and the Precision and F-1 score can be further improved by considering equivalence conjunctions.
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Acknowledgments
This work was supported by the National High-tech R&D Program of China (Grant No. SS2015AA020102), National Basic Research Program of China (Grant No. 2011CB302302), the 1000-Talent program, and the Tsinghua University Initiative Scientific Research Program. We thank the research assistance provided by Qingbo Cao at Tsinghua University.
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Zhang, Y., Zhang, Y., Yin, Y., Xu, J., Xing, C., Chen, H. (2016). Chronic Disease Related Entity Extraction in Online Chinese Question and Answer Services. In: Zheng, X., Zeng, D., Chen, H., Leischow, S. (eds) Smart Health. ICSH 2015. Lecture Notes in Computer Science(), vol 9545. Springer, Cham. https://doi.org/10.1007/978-3-319-29175-8_6
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