Text Document Preprocessing and Classification Using SVM and Improved CNN
- By Jaspreet Sidhu1
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View Affiliations Hide Affiliations1 Centre for Interdisciplinary Research in Business and Technology, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
- Source: Demystifying Emerging Trends in Machine Learning , pp 226-237
- Publication Date: February 2025
- Language: English
Text Document Preprocessing and Classification Using SVM and Improved CNN, Page 1 of 1
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Text categorization is a crucial technology in data mining as well as data retrieval that has been extensively investigated and is developing at a rapid pace. Convolutional neural networks (CNNs) are a kind of deep learning modeling that may reduce the complexity of the model while accurately extracting characteristics from input text. Support vector machine (SVM) results have always been more trustworthy and superior to those of other traditional artificial intelligence approaches. Using enhanced convolutional neural network (CNNs) as well as support vector machines (SVMs), we offer a novel approach to online text categorization in this study. Our approach begins with text attribute identification and prediction using a model based on CNN with a five-layer network structure. Databases including both text and images will find it to be a major factor in the long run.
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