Protein/Gene Entity Recognition and Normalization with Domain Knowledge and Local Context

التفاصيل البيبلوغرافية
العنوان: Protein/Gene Entity Recognition and Normalization with Domain Knowledge and Local Context
المؤلفون: Weihong Yao, Zongze Li, Xuefei Li, Zhe Liu, Shixian Ning
المصدر: Lecture Notes in Computer Science ISBN: 9783030381882
CLSW
بيانات النشر: Springer International Publishing, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Normalization (statistics), Computer science, business.industry, media_common.quotation_subject, 02 engineering and technology, Ambiguity, computer.software_genre, Biomedical text mining, Identifier, 03 medical and health sciences, 0302 clinical medicine, Named-entity recognition, 030221 ophthalmology & optometry, 0202 electrical engineering, electronic engineering, information engineering, Domain knowledge, Leverage (statistics), 020201 artificial intelligence & image processing, Artificial intelligence, business, computer, Natural language processing, media_common
الوصف: Biomedical named entity recognition and normalization aim at recognizing biomedical entity mentions from text and mapping them to their unique database entity identifiers (IDs), which are the primary task of biomedical text mining. However, name variation and entity ambiguity problems make this task challenging. In this paper, we leverage domain knowledge by a novel knowledge feature representation method to recognize more entity variants, and model important local context through a dual attention mechanism and a gating mechanism to perform entity normalization. Experimental results on the BioCreative VI Bio-ID corpus show that our proposed system achieves the new state-of-the-art performance (0.844 F1-score for protein/gene entity recognition and 0.408 F1-score for normalization).
ردمك: 978-3-030-38188-2
DOI: 10.1007/978-3-030-38189-9_39
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::0ec97f2375149ab9437d132829d070af
https://doi.org/10.1007/978-3-030-38189-9_39
Rights: CLOSED
رقم الانضمام: edsair.doi...........0ec97f2375149ab9437d132829d070af
قاعدة البيانات: OpenAIRE
الوصف
ردمك:9783030381882
DOI:10.1007/978-3-030-38189-9_39