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7 December 2023 Text classification method for power customer complaints based on natural language processing technology and drosophila algorithm
Longzhu Zhu, Mingjie Zhang, Yuanyuan Yang, Jian Gong, Lihua Gong, Jing Yang
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Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129412J (2023) https://doi.org/10.1117/12.3011537
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
Power customer complaint texts usually contain a large number of natural language texts, which may have problems such as polysemy of vocabulary, complexity of grammatical structure and subjectivity, and are difficult to classify. Therefore, a classification method for power customer complaint texts based on natural language processing technology and drosophila algorithm is proposed. The text is obtained through web crawler technology, the text is segmented by natural language processing technology, and the modal particles and stop word in the text are removed. The bag-of-words model is used to characterize the text and obtain the result of text feature representation. Based on the text preprocessing results, vectorize the complaint text of power customers. Finally, based on the text preprocessing and vectorization, the drosophila algorithm is used to realize the text classification of power customer complaints. The experimental results show that the proposed method has high text classification accuracy, recall rate, and F1 value, indicating that its classification effect is relatively accurate.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Longzhu Zhu, Mingjie Zhang, Yuanyuan Yang, Jian Gong, Lihua Gong, and Jing Yang "Text classification method for power customer complaints based on natural language processing technology and drosophila algorithm", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129412J (7 December 2023); https://doi.org/10.1117/12.3011537
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KEYWORDS
Education and training
Machine learning
Particles
Statistical analysis
Data modeling
Industry
Feature extraction
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