An Efficient Tool for Semantic Biomedical Document Analysis-Reference-Cited by-同舟云学术

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An Efficient Tool for Semantic Biomedical Document Analysis

Published:2021 Issue: Volume: Page:514-522
ISSN:2190-3018
Container-title:Advances in Intelligent Information Hiding and Multimedia Signal Processing
language:
Short-container-title:

Author:

Li Meijing^ORCID,Hu Jingyu^ORCID,Ryu Keun Ho^ORCID

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-33-6757-9_63

Reference24 articles.

1. Stanford CoreNLP 4.0.0: https://corenlp.run/. Last accessed 2020-04-16

2. NLPIR: https://github.com/NLPIR-team/NLPIR. Last accessed 2020-04-28

3. Word2Vec: https://radimrehurek.com/gensim/models/word2vec.html. Last accessed 2020-04-28

4. Zhang, Y., Jia, Y., Fu, L., Wang, X.: AceMap academic map and AceKG academic knowledge graph for academic data visualization. J. Shanghai Jiaotong Univ. (Sci.) 52(10), 1357–1362 (2018)

5. Singhal, A.: Introducing the knowledge graph: things, not strings. https://goo-gleblog.blogspot.com/2012/05/introduc-ing-knowledge-graph-things-not.html. Last accessed 2020-05-05

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Discovering Thematically Coherent Biomedical Documents Using Contextualized Bidirectional Encoder Representations from Transformers-Based Clustering;International Journal of Environmental Research and Public Health;2022-05-12

2. BioBERT Based Efficient Clustering Framework for Biomedical Document Analysis;Lecture Notes in Electrical Engineering;2022

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