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A text mining-based approach for comprehensive understanding of Chinese railway operational equipment failure reports. [PDF]

Sci Rep
Yang X, Li H, Xu Y, Shen N, He R.
europepmc   +1 more source

Decision level scheme for fusing multiomics and histology slide images using deep neural network for tumor prognosis prediction. [PDF]

Sci Rep
Zhao T, Ren Y, Lu H, Kong Y.
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Drug-drug interaction analysis based on information bottleneck graph neural network: A review. [PDF]

Medicine (Baltimore)
Wang S.
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Portable and Rapid Smartphone-Based Colorimetric Assay of Peracetic Acid for Point-of-Use Medical/Pharmaceutical Disinfectant Preparation. [PDF]

Molecules
Katib S, Apichai S, Jiaranaikulwanitch J, Sirithunyalug B, Ogata F, Kawasaki N, Grudpan K, Saenjum C.   +7 more
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iTissue

Zambrana C, Malod-Dognin N, Pržulj N.
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Improving Chinese Named Entity Recognition by Large-Scale Syntactic Dependency Graph

IEEE/ACM Transactions on Audio Speech and Language Processing, 2022
Named entity recognition (NER) isa preliminary task in natural language processing (NLP). Recognizing Chinese named entities from unstructured texts is challenging due to the lack of word boundaries.
Peng Zhu, Dawei Cheng, Fan Yang, Yifeng Luo, Dingjiang Huang, Weining Qian, Aoying Zhou   +6 more
semanticscholar   +1 more source

Multiple Embeddings Enhanced Multi-Graph Neural Networks for Chinese Healthcare Named Entity Recognition

IEEE journal of biomedical and health informatics, 2021
Named Entity Recognition (NER) is a natural language processing task for recognizing named entities in a given sentence. Chinese NER is difficult due to the lack of delimited spaces and conventional features for determining named entity boundaries and ...
Lung-Hao Lee, Yi Lu
semanticscholar   +1 more source

Named Entity Recognition and Relation Extraction with Graph Neural Networks in Semi Structured Documents

International Conference on Pattern Recognition, 2021
The use of administrative documents to communicate and leave record of business information requires of methods able to automatically extract and understand the content from such documents in a robust and efficient way.
Manuel Carbonell, Pau Riba, M. Villegas, A. Fornés, J. Lladós   +4 more
semanticscholar   +1 more source

LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020
Graph Convolution Network (GCN) has become new state-of-the-art for collaborative filtering. Nevertheless, the reasons of its effectiveness for recommendation are not well understood.
Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, Meng Wang   +5 more
semanticscholar   +1 more source