暂无分享,去创建一个
James Pustejovsky | Ying Lin | Martha Palmer | Haoran Zhang | Heng Ji | Shih-Fu Chang | Weili Liu | Qingyun Wang | Xuan Wang | Manling Li | Guangxing Han | Jiawei Han | Boyan Onyshkevych | Bangzheng Li | Yingjun Guan | Nikolaus Parulian | Nikolaus Nova Parulian | Aabhas Chauhan | Jiawei Ma | Jingxuan Tu | Ruisong Li | Xiangchen Song | David Liem | Ahmed Elsayed | Jasmine Rah | Cynthia Schneider | Martha Palmer | Shih-Fu Chang | Jiawei Han | B. Onyshkevych | J. Pustejovsky | Xuan Wang | Qingyun Wang | Manling Li | G. Han | Jiawei Ma | Jingxuan Tu | Ying Lin | H. Zhang | Weili Liu | Aabhas Chauhan | Yingjun Guan | Bangzheng Li | Ruisong Li | Xiangchen Song | Heng Ji | D. Liem | Ahmed Elsayed | Jasmine Rah | Cynthia Schneider
[1] Danqi Chen,et al. of the Association for Computational Linguistics: , 2001 .
[2] R. Smith,et al. An Overview of the Tesseract OCR Engine , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).
[3] Hugo Zaragoza,et al. The Probabilistic Relevance Framework: BM25 and Beyond , 2009, Found. Trends Inf. Retr..
[4] Junichi Tsujii,et al. Event extraction for systems biology by text mining the literature. , 2010, Trends in biotechnology.
[5] Zhiyong Lu,et al. Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases , 2011 .
[6] Shuying Shen,et al. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text , 2011, J. Am. Medical Informatics Assoc..
[7] Sampo Pyysalo,et al. Overview of BioNLP Shared Task 2013 , 2013, BioNLP@ACL.
[8] A. Valencia,et al. Overview of the chemical compound and drug name recognition ( CHEMDNER ) task , 2013 .
[9] Paloma Martínez,et al. SemEval-2013 Task 9 : Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013) , 2013, *SEMEVAL.
[10] Jari Björne,et al. Large-Scale Event Extraction from Literature with Multi-Level Gene Normalization , 2013, PloS one.
[11] Taylor Cassidy,et al. The Wisdom of Minority: Unsupervised Slot Filling Validation based on Multi-dimensional Truth-Finding , 2014, COLING.
[12] Peter M. A. Sloot,et al. A novel feature-based approach to extract drug-drug interactions from biomedical text , 2014, Bioinform..
[13] Chi Zhang,et al. Learning to Answer Biomedical Factoid & List Questions: OAQA at BioASQ 3B , 2015, CLEF.
[14] Heng Ji,et al. Modeling Truth Existence in Truth Discovery , 2015, KDD.
[15] S. Ekins,et al. FDA approved drugs as potential Ebola treatments , 2015, F1000Research.
[16] Heng Ji,et al. Entity linking for biomedical literature , 2014, DTMBIO '14.
[17] Heng Ji,et al. FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation , 2015, KDD.
[18] Xiaohui Liang,et al. CHEMDNER system with mixed conditional random fields and multi-scale word clustering , 2015, Journal of Cheminformatics.
[19] Georgios Balikas,et al. An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition , 2015, BMC Bioinformatics.
[20] Yifan Peng,et al. Improving chemical disease relation extraction with rich features and weakly labeled data , 2016, Journal of Cheminformatics.
[21] Louise Deléger,et al. Overview of the Bacteria Biotope Task at BioNLP Shared Task 2016 , 2016, BioNLP.
[22] Zhiyong Lu,et al. TaggerOne: joint named entity recognition and normalization with semi-Markov Models , 2016, Bioinform..
[23] Yifan Peng,et al. Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task , 2016, Database J. Biol. Databases Curation.
[24] Eric Nyberg,et al. Learning to Answer Biomedical Questions: OAQA at BioASQ 4B , 2016 .
[25] Hoifung Poon,et al. Distant Supervision for Relation Extraction beyond the Sentence Boundary , 2016, EACL.
[26] Thomas C. Wiegers,et al. The Comparative Toxicogenomics Database: update 2017 , 2016, Nucleic Acids Res..
[27] Peter Szolovits,et al. Bridging semantics and syntax with graph algorithms - state-of-the-art of extracting biomedical relations , 2017, Briefings Bioinform..
[28] David J. Crandall,et al. A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks , 2017, 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR).
[29] Eric Nyberg,et al. Tackling Biomedical Text Summarization: OAQA at BioASQ 5B , 2017, BioNLP.
[30] Nanyun Peng,et al. Cross-Sentence N-ary Relation Extraction with Graph LSTMs , 2017, TACL.
[31] Shuchang Zhou,et al. EAST: An Efficient and Accurate Scene Text Detector , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Maryam Habibi,et al. Deep learning with word embeddings improves biomedical named entity recognition , 2017, Bioinform..
[33] Heng Ji,et al. Expertise-Aware Truth Analysis and Task Allocation in Mobile Crowdsourcing , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).
[34] Mariana L. Neves,et al. Olelo: a web application for intuitive exploration of biomedical literature , 2017, Nucleic Acids Res..
[35] R. S. Huang,et al. Overview of Bacteria , 2017 .
[36] Heng Ji,et al. Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems , 2017, Big Data.
[37] Sampo Pyysalo,et al. A neural network multi-task learning approach to biomedical named entity recognition , 2017, BMC Bioinformatics.
[38] Waleed Ammar,et al. Extracting Scientific Figures with Distantly Supervised Neural Networks , 2018, JCDL.
[39] Teng Ren,et al. Learning Named Entity Tagger using Domain-Specific Dictionary , 2018, EMNLP.
[40] Yu Zhang,et al. Open Information Extraction with Meta-pattern Discovery in Biomedical Literature , 2018, BCB.
[41] Cathy H. Wu,et al. Pattern Discovery for Wide-Window Open Information Extraction in Biomedical Literature , 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
[42] Heng Ji,et al. Biomedical Event Extraction based on Knowledge-driven Tree-LSTM , 2019, NAACL.
[43] Donald C. Comeau,et al. LitSense: making sense of biomedical literature at sentence level , 2019, Nucleic Acids Res..
[44] Wei-Hung Weng,et al. Publicly Available Clinical BERT Embeddings , 2019, Proceedings of the 2nd Clinical Natural Language Processing Workshop.
[45] Zhiyong Lu,et al. Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets , 2019, BioNLP@ACL.
[46] Yu Zhang,et al. Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning , 2018, bioRxiv.
[47] Iz Beltagy,et al. SciBERT: A Pretrained Language Model for Scientific Text , 2019, EMNLP.
[48] Inioluwa Deborah Raji,et al. Model Cards for Model Reporting , 2018, FAT.
[49] Robert Leaman,et al. PubTator central: automated concept annotation for biomedical full text articles , 2019, Nucleic Acids Res..
[50] Heng Ji,et al. Syntax-aware Multi-task Graph Convolutional Networks for Biomedical Relation Extraction , 2019, EMNLP.
[51] Heng Ji,et al. PaperRobot: Incremental Draft Generation of Scientific Ideas , 2019, ACL.
[52] T. Dokland,et al. Structure of the host cell recognition and penetration machinery of a Staphylococcus aureus bacteriophage , 2019, bioRxiv.
[53] Qi Li,et al. Distantly Supervised Biomedical Named Entity Recognition with Dictionary Expansion , 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
[54] Qingyu Chen,et al. An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining , 2020, BIONLP.
[55] Heng Ji,et al. Cross-media Structured Common Space for Multimedia Event Extraction , 2020, ACL.
[56] Eric Horvitz,et al. SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search , 2020, EMNLP.
[57] Jaewoo Kang,et al. BioBERT: a pre-trained biomedical language representation model for biomedical text mining , 2019, Bioinform..
[58] Dragomir R. Radev,et al. CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization , 2020, ArXiv.
[59] Arthur S Slutsky,et al. Angiotensin-converting enzyme 2 (ACE2) as a SARS-CoV-2 receptor: molecular mechanisms and potential therapeutic target , 2020, Intensive Care Medicine.
[60] Pedro A. Szekely,et al. KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis , 2020, SEMWEB.
[61] Oren Etzioni,et al. CORD-19: The Covid-19 Open Research Dataset , 2020, NLPCOVID19.
[62] Ying Lin,et al. GAIA: A Fine-grained Multimedia Knowledge Extraction System , 2020, ACL.
[63] David Martínez,et al. Global Locality in Biomedical Relation and Event Extraction , 2020, BioNLP.
[64] Daniel Satchkov,et al. Artificial Intelligence-Powered Search Tools and Resources in the Fight Against COVID-19 , 2020, EJIFCC.
[65] Francis Wolinski,et al. Visualization of Diseases at Risk in the COVID-19 Literature , 2020, ArXiv.
[66] Xuan Wang,et al. EVIDENCEMINER: Textual Evidence Discovery for Life Sciences , 2020, ACL.
[67] Xuan Wang,et al. Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision , 2020, ArXiv.
[68] Sabber Ahamed,et al. Information Mining for COVID-19 Research From a Large Volume of Scientific Literature , 2020, ArXiv.
[69] Weili Liu,et al. Automatic Textual Evidence Mining in COVID-19 Literature , 2020, ArXiv.
[70] Dan Lahav,et al. Interactive Extractive Search over Biomedical Corpora , 2020, BIONLP.
[71] James Pustejovsky,et al. Exploration and Discovery of the COVID-19 Literature through Semantic Visualization , 2020, NAACL.