@article{3810,
  author = {Wen Bo, Shi Li},
  title = {Analysis and Training of Network Information Document Management System Based on Data Mining},
  journal = {Journal of Information & Systems Management},
  year = {2023},
  volume = {13},
  number = {3},
  doi = {https://doi.org/10.6025/jism/2023/13/3/70-77},
  url = {https://www.dline.info/jism/fulltext/v13n3/jismv13n3_2.pdf},
  abstract = {With the rapid development of information technology, document information management has become increasingly important. To improve the efficiency and accuracy of document information management, we propose a solution based on the BP neural network algorithm. This scheme first preprocesses the document information, including text cleaning, word segmentation, feature extraction, etc. Then, we used the BP neural network algorithm to classify and recognize the document information. Specifically, we used Multilayer Perceptron (MLP) as the model structure of the BP neural network algorithm, trained and optimized through a backpropagation algorithm. At the same time, we also used cross-validation and early stop techniques to avoid overfitting and underfitting issues. Through experimental verification, we found that the document information management system based on the BP neural network algorithm has high accuracy and efficiency. This system has higher classification accuracy and a lower false alarm rate than traditional text classification algorithms. In addition, the system also has good generalization performance and can adapt to the document information management needs of different fields.},
}