Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models
for chemical and disease named entity recognition

Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition

25 August 2018

Dat Quoc Nguyen

Karin Verspoor

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Papers citing "Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition"

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Title
Arabic aspect based sentiment analysis using bidirectional GRU based modelsJournal of King Saud University: Computer and Information Sciences (JSUCIS), 2021 Mohammed Mustafa T. H. Soliman A. Taloba Mohammed Fawzi Seedik 175 97 0 23 Jan 2021
Fancy Man Lauches Zippo at WNUT 2020 Shared Task-1: A Bert Case Model for Wet Lab Entity Extraction Haoding Meng Qingcheng Zeng Xiaoyang Fang Zhexin Liang 83 1 0 28 Sep 2020
Neural Named Entity Recognition for KazakhConference on Intelligent Text Processing and Computational Linguistics (CICLing), 2020 Gulmira Tolegen Alymzhan Toleu O. Mamyrbayev Rustam Mussabayev 137 12 0 17 Jul 2020
Information Extraction of Clinical Trial Eligibility Criteria Yitong Tseo M. Salkola A. Mohamed Anuj Kumar F. Abnousi FaML 219 27 0 12 Jun 2020
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity PredictionInternational Conference on Language Resources and Evaluation (LREC), 2020 Danushka Bollegala Ryuichi Kiryo K. Tsujino Haruki Yukawa 104 7 0 25 Feb 2020
Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings Zenan Zhai Dat Quoc Nguyen S. Akhondi Camilo Thorne Christian Druckenbrodt Trevor Cohn M. Gregory Karin Verspoor 127 43 0 05 Jul 2019