Ontology and Knowledge Graphs for Semantic Analysis in Natural Language Processing

Bharambe, Ujwala; Narvekar, Chhaya; Andugula, Prakash

doi:10.1201/9781003272649-6

Cited by 4 publications

(2 citation statements)

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“…These data are generally gleaned from the clinical notes from medical practitioners. 49,50 This requires establishment of an interconnected network with a focus on the real-time sharing of medical data which highly depends on the 5G network communication.…”

Section: Source Datamentioning

confidence: 99%

“…These algorithms can be applied to structured data, such as EHRs, to identify unusual spikes in the number of patients with a specific infection or symptom. These data are generally gleaned from the clinical notes from medical practitioners 49,50 . This requires establishment of an interconnected network with a focus on the real‐time sharing of medical data which highly depends on the 5G network communication.…”

Section: Leveraging the Emergence Of 5g Network Technology For Advanc...mentioning

confidence: 99%

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Opportunities and challenges of 5G network technology toward precision medicine

Kang,

Lee,

Lim

et al. 2023

Clinical Translational Sci

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Moving away from traditional “one‐size‐fits‐all” treatment to precision‐based medicine has tremendously improved disease prognosis, accuracy of diagnosis, disease progression prediction, and targeted‐treatment. The current cutting‐edge of 5G network technology is enabling a growing trend in precision medicine to extend its utility and value to the smart healthcare system. The 5G network technology will bring together big data, artificial intelligence, and machine learning to provide essential levels of connectivity to enable a new health ecosystem toward precision medicine. In the 5G‐enabled health ecosystem, its applications involve predictive and preventative measurements which enable advances in patient personalization. This review aims to discuss the opportunities, challenges, and prospects posed to 5G network technology in moving forward to deliver personalized treatments and patient‐centric care via a precision medicine approach.

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Section: Source Datamentioning

confidence: 99%

Section: Leveraging the Emergence Of 5g Network Technology For Advanc...mentioning

confidence: 99%

Opportunities and challenges of 5G network technology toward precision medicine

Kang,

Lee,

Lim

et al. 2023

Clinical Translational Sci

View full text Add to dashboard Cite

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Predicting the Effects of News on the Financial Market Based on Machine Learning Technology

Vysotska,

Holoshchuk,

Goloshchuk

et al. 2023

2023 IEEE 5th International Conference on Advanced Information and Communication Technologies (AICT)

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A Study of Improvement Strategies for Semantic Analysis Techniques in Natural Language Processing

Wang,

2024

Applied Mathematics and Nonlinear Sciences

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Semantic analysis, a crucial aspect of natural language processing, encounters numerous practical challenges due to the limitations of its current technology. Therefore, this paper enhances the traditional semantic analysis technology by developing a frame recognition model that integrates syntactic and semantic roles, a text semantic feature extraction model, and an audio/video information extraction model with a multimodal inter-modal cross-attention mechanism. These models are then integrated to jointly construct an improved model for semantic analysis, which is based on deep neural networks. The paper examines the model’s improvement effect in semantic role labeling, text classification, and information extraction. The F1 values of this paper’s model on the Wall Street Journal and Brown test sets are 90.4% and 81.4%, respectively, which are the highest semantic role recognition annotation accuracy rates. The HL, P, R, and F1 values of this paper’s model on the three datasets, on the other hand, are the best results among all models, and it has the best text categorization effect. This paper’s model has a 95.3% accuracy rate in detecting theme subtitles. The recognition accuracy of simple and complex backgrounds is 95.7% and 94.1%, respectively. After the information extraction method of this paper’s model underwent error correction, the accuracy of ASR recognition increased by 18.55%.

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Ontology and Knowledge Graphs for Semantic Analysis in Natural Language Processing

Cited by 4 publications

References 0 publications

Opportunities and challenges of 5G network technology toward precision medicine

Opportunities and challenges of 5G network technology toward precision medicine

Predicting the Effects of News on the Financial Market Based on Machine Learning Technology

A Study of Improvement Strategies for Semantic Analysis Techniques in Natural Language Processing

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