mlsanityData to 13 Oct 2026

Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processing

arXiv 2409.15576 ↗First posted 23 Sep 2024cs.CL cs.IRcited by 7

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Abstract (arXiv)

The development of Internet technology has led to a rapid increase in news information. Filtering out valuable content from complex information has become an urgentproblem that needs to be solved. In view of the shortcomings of traditional manual classification methods that are time-consuming and inefficient, this paper proposes an automaticclassification scheme for news texts based on deep learning. This solution achieves efficient classification and management of news texts by introducing advanced machine learning algorithms, especially an optimization model that combines Bi-directional Long Short-Term Memory Network (Bi-LSTM) and Attention Mechanism. Experimental results show that this solution can not only significantly improve the accuracy and timeliness of classification, but also significantly reduce the need for manual intervention. It has important practical significance for improving the information processing capabilities of the news industry and accelerating the speed of information flow. Through comparative analysis of multiple common models, the effectiveness and advancement of the proposed method are proved, laying a solid foundation for future news text classification research.

Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). Builds on 13 of its 23 references that are in the map. First posted on arXiv 23 Sep 2024.

Builds on

13 of 23 references.

References · 13

  1. 2023NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Spacecited by 89
  2. 2024Survival Prediction Across Diverse Cancer Types Using Neural Networkscited by 80
  3. 2022News Category Datasetcited by 42
  4. 2024Dynamic Fraud Detection: Integrating Reinforcement Learning into Graph Neural Networkscited by 19
  5. 2024Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Functioncited by 16
  6. 2024A comparative study of generative adversarial networks for image recognition algorithms based on deep learning and traditional methodscited by 12
  7. 2024Enhancing Medical Imaging with GANs Synthesizing Realistic Images from Limited Datacited by 11
  8. 2024Exploration of Multi-Scale Image Fusion Systems in Intelligent Medical Image Analysiscited by 10
  9. 2024Algorithm Research of ELMo Word Embedding and Deep Learning Multimodal Transformer in Image Descriptioncited by 10
  10. 2024Text classification optimization algorithm based on graph neural networkcited by 8
  11. 2024Enhancing Convolutional Neural Networks with Higher-Order Numerical Difference Methodscited by 8
  12. 2024Enhancing Deep Learning with Optimized Gradient Descent: Bridging Numerical Methods and Neural Network Trainingcited by 7
1 more
  1. 2024A Comprehensive Survey of Text Classification Techniques and Their Research Applications: Observational and Experimental Insightscited by 5

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Cited by year

Citing papers per year: 2024: 7.

7 papers.

  1. 2024Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networkscited by 33
  2. 2024Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithmcited by 11
  3. 2024Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphscited by 9
  4. 2024An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reductioncited by 9
  5. 2024Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Studycited by 8
  6. 2024Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Datacited by 7
  7. 2024Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Managementcited by 6