Abstract
Text classification is a basic problem in the field of natural language processing. It is a very active research direction in the field of machine learning, and has many important practical applications. This paper mainly studies the application of semantic analysis in text classification of computer technology. In view of the fact that most current methods ignore the important correlation between features, this paper adopts the LSA method, which fully considers the semantic relationship between features and reduces the dimension of feature space, so as to construct a new semantic space. Experimental results show that the proposed method can effectively reduce the dimension of feature space and improve the performance of text classification.
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Wang, Z. (2022). Application of Semantics Analysis in Text Classification of Computer Technology. In: J. Jansen, B., Liang, H., Ye, J. (eds) International Conference on Cognitive based Information Processing and Applications (CIPA 2021). Lecture Notes on Data Engineering and Communications Technologies, vol 85. Springer, Singapore. https://doi.org/10.1007/978-981-16-5854-9_82
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DOI: https://doi.org/10.1007/978-981-16-5854-9_82
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