TF-IDF combined rank factor Naive Bayesian algorithm for intelligent language classification recommendation systems

Luo, Yonglian; Lu, Cailin

doi:10.1016/j.sasc.2024.200136

Systems and Soft Computing

2024

DOI: 10.1016/j.sasc.2024.200136

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TF-IDF combined rank factor Naive Bayesian algorithm for intelligent language classification recommendation systems

Yonglian Luo,

Cailin Lu

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Cited by 3 publications

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TC-BERT: large-scale language model for Korean technology commercialization documents

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Research on the Quality Improvement of Party School Education and Training in Newly-Built Applied Undergraduate Colleges and Universities Facing Intelligent Educational Technology

Chen

2024

Applied Mathematics and Nonlinear Sciences

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With the continuous progress of intelligent education technology, the education and training of party schools in new applied undergraduate colleges and universities are facing the urgent need to improve the quality. In this study, we use Jieba Partition Technology to perform particual processing on training materials and use the TF-IDF algorithm to extract features from the particual results. A training management platform for party schools in colleges and universities that integrates intelligent education technology is built using the improved collaborative filtering recommendation model. Taking a university as an example, the performance test of this paper’s training platform is conducted, and finally, through regression analysis, the effect of improving the quality of party school education and training is assessed. The recommendation model in this paper performs better when the number of recommendations is 200, yielding precision and recall values of 0.55 and 0.51, respectively. The average degree of compliance of the party school trainees with the five indicators of effectiveness assessment is high, and the average score of “Satisfactory training results” is 4.035. The factors of the intelligent education platform, such as training content, training methods, instructor level and training materials, all have highly significant effects on the improvement of training quality at the level of p<0.001. All of them have a highly significant positive contribution to the improvement of training quality.

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Design of Intelligent Document Categorization System for Office Software Combined with Neural Networks

Yuan

2024

Applied Mathematics and Nonlinear Sciences

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Office software documents as a carrier of effective information; the complexity of its text determines the efficiency of information extraction. The current research hot spot involves accurately categorizing the document text. In this paper, the document data are processed by document cut, text segmentation, de-duplication, text feature extraction, word frequency statistics and other data processing, and the Word2Vec model is used to represent the text of office software documents. The improved CNNSVM text classification model was constructed by replacing the classifier and fused the attention mechanism module based on the convolutional neural network. In this way, a document categorization system based on a neural network is designed. On the CR dataset, the model in this paper was trained for 25-90 rounds later, and the loss value, recall rate, accuracy rate, and F1 value converged to about 0.1, 0.91, 0.85, and 0.88 in turn. And the accuracy rate of this dataset has been improved by 18.71% when compared to the worst comparison model. The attention module can be used to display different text sequence weights in the model in this paper to correctly classify text. The above experimental results fully demonstrate the superior performance of the model in this paper and its high matching on multiple datasets.

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TF-IDF combined rank factor Naive Bayesian algorithm for intelligent language classification recommendation systems

Cited by 3 publications

References 13 publications

TC-BERT: large-scale language model for Korean technology commercialization documents

TC-BERT: large-scale language model for Korean technology commercialization documents

Research on the Quality Improvement of Party School Education and Training in Newly-Built Applied Undergraduate Colleges and Universities Facing Intelligent Educational Technology

Design of Intelligent Document Categorization System for Office Software Combined with Neural Networks

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