Paper
6 May 2022 Research on classification algorithm of commodity short text based on CNN
Author Affiliations +
Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 121760G (2022) https://doi.org/10.1117/12.2636398
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China
Abstract
With the development and popularization of the Internet and the rapid development of e-commerce platforms, resulting in a huge amount of commodity short text. Research on short text classification of commodities is of great significance to commodity circulation, consumer behavior research and advertising push. This paper takes the commodity short text data set as the object, and the Convolutional Neural Network (CNN) algorithm based on deep learning is used to construct the classification model. Experimental results show that CNN algorithm is better than traditional machine learning algorithms (Naive Bayes(NB), K Nearest Neighbor(KNN) and Support Vector Machine(SVM)) in commodity short text classification.
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Qilin Qin, Yunshan Sun, Sihan Wang, Qian Huang, and Yuetong Cheng "Research on classification algorithm of commodity short text based on CNN", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 121760G (6 May 2022); https://doi.org/10.1117/12.2636398
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KEYWORDS
Data modeling

Convolution

Classification systems

Convolutional neural networks

Machine learning

Algorithm development

Feature extraction

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