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Analysis of the Relevance Environment between Marxist Philosophy and System Theory Based on Deep Learning

In social science and natural science, MP (Marxist Philosophy) has played an active role in promoting its development, and MP also guides people's practice and understanding. There is an inevitable connection with system theory MP. In a sense, both system theory and PMbelong to methodology and...

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Detalles Bibliográficos
Autor principal: Jiang, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9357689/
https://www.ncbi.nlm.nih.gov/pubmed/35958377
http://dx.doi.org/10.1155/2022/6322272
Descripción
Sumario:In social science and natural science, MP (Marxist Philosophy) has played an active role in promoting its development, and MP also guides people's practice and understanding. There is an inevitable connection with system theory MP. In a sense, both system theory and PMbelong to methodology and both contain the viewpoints of movement and development. In this paper, various text features in natural scenes are discussed in detail, and the original vector is studied by using CNN (Convective Neural Network) of DL (Deep Learning), so as to construct a one-dimensional text vector and realize the mutual influence and continuous optimization of feature extraction and text clustering. The experimental results show that under the condition of calculating the current cosine similarity measure, the accuracy rate is the highest, reaching 93.67%. This algorithm can effectively improve its performance in text classification tasks on large data sets.