Biomedical Text Similarity Evaluation Using Attention Mechanism and Siamese Neural Network

Li, Zhengguang; Chen, Heng; Chen, Huayue

doi:10.1109/access.2021.3099021

Cited by 7 publications

(3 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the determination of similarity in Chinese short texts, methods have always been improved, from SOW/BOW statistical frequency [40] to n-gram sliding windows [41], from topic models [42] to deep learning [43]. The evolution of methods is to meet the similarity situation in different situations.…”

Section: Filling Methods Based On Ocr and Text Similaritymentioning

confidence: 99%

Research on a Web System Data-Filling Method Based on Optical Character Recognition and Multi-Text Similarity

Su,

Kang,

Fan

2024

Applied Sciences

View full text Add to dashboard Cite

In the development of web systems, data uploading is a relatively important function. The traditional method of uploading data is to manually fill out forms, but when the data to be uploaded mostly exist in the form of form images, and the form content contains a lot of similar field information and irrelevant edge information, using traditional methods is not only time-consuming and labor-intensive, but also prone to errors. This requires a technology that can automatically fill in complex form images. OCR is an optical character recognition technology that can convert images into digitized text data using computer vision methods. However, using this technology alone cannot complete the tasks of extracting relevant data and filling corresponding fields. To address this issue, this article proposes a method that combines OCR technology and Levenshtein multi-text similarity. This method can effectively solve the problem of data filling after parsing complex form images, and the application results of this method in web systems show that the filling accuracy for complex form images can reach over 90%.

show abstract

Section: Filling Methods Based On Ocr and Text Similaritymentioning

confidence: 99%

Research on a Web System Data-Filling Method Based on Optical Character Recognition and Multi-Text Similarity

Su,

Kang,

Fan

2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…In the experiment dataset, eight baseline methods were employed, including representation-based text classification (Cao and Zhao, 2018); interactive-based text classification models such as ESIM (Chen et al, 2016), Siamese Bi-LSTM (Li et al, 2021), Attention-Bi-LSTM (Xie et al, 2019); and pre-trained based text classification models such as BERT.…”

Section: Baseline Methodsmentioning

confidence: 99%

Intelligent substation virtual circuit verification method combining knowledge graph and deep learning

Cao,

Zhang,

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

The correctness of the intelligent electronic devices (IEDs) virtual circuit connections in intelligent substations directly affects the stability of the system operation. Existing verification methods suffer from low efficiency in manual verification and lack uniformity in design specifications. Therefore, this paper proposes a virtual circuit automatic verification method that combines knowledge graphs with deep learning. Firstly, this method utilizes expert knowledge and relevant standard specifications to construct a knowledge graph of virtual circuits, integrating knowledge from historical intelligent substation configuration files into the knowledge graph. Then, leveraging multi-head attention mechanisms and Siamese neural networks, it achieves matching between the textual descriptions of virtual terminals and standard virtual terminal descriptions. Additionally, a verification process for the virtual terminal port address string is incorporated. Finally, experimental validation confirms the effectiveness of the proposed method and strategy, further enhancing the accuracy of virtual circuit verification.

show abstract

“…Using the Siamese neural network in that study, satisfactory results for biomedical text similarity evaluation could not be obtained. Li et al [9] designed a self2self-attention model to solve syntactic complexity and long-sentence problems. In [10], the semantic representation of each sentence was used to generate its embedding.…”

Section: Introductionmentioning

confidence: 99%

Skin Medical Image Captioning Using Multi-Label Classification and Siamese Network

2023

View full text Add to dashboard Cite

Image captioning is a process of automatically generating descriptive sentences for a given image. Text-toimage search is a form of search in which images are retrieved based on matching keywords and image features. We focus on the case in which multiple description sentences are generated for one image. In this study, we used four learning models:(1) a discriminator, which is a binary classifier that distinguishes skin from background; (2) an autoencoder; (3) a multiclass classification model combining the features from the discriminator and autoencoder and producing keyword labels; and (4) a Siamese network learning the textual similarity matching between colloquial description sentences of skin imaging pathology and keywords produced from the multi-class classifier. The experimental results show that the proposed method yields an accuracy of up to 99% for the testing data in terms of colloquial language of skin images. This study enabled users to read the skin. For teaching research on skin diagnosis, the proposed method can significantly relieve the shortage of training personnel and assist hospitals that lack resources for conducting case studies. The results of this study are expected to be feasible and can be applied in actual clinical teaching. For medical education in dermatology, the findings of this study contribute to the practical value of quantitative indicators and assessments for learning outcomes of medical students.

show abstract

Biomedical Text Similarity Evaluation Using Attention Mechanism and Siamese Neural Network

Cited by 7 publications

References 29 publications

Research on a Web System Data-Filling Method Based on Optical Character Recognition and Multi-Text Similarity

Research on a Web System Data-Filling Method Based on Optical Character Recognition and Multi-Text Similarity

Intelligent substation virtual circuit verification method combining knowledge graph and deep learning

Skin Medical Image Captioning Using Multi-Label Classification and Siamese Network

Contact Info

Product

Resources

About