TEXT CLASSIFICATION AND CLUSTER ANALYSIS BASED ON DEEP LEARNING AND NATURAL LANGUAGE PROCESSING

被引：0
作者：
HUANG H.U.A. [1 ]
机构：
[1] School of Computer and Artificial Intelligence, Henan Finance University, Henan, Zhengzhou
来源：
Scalable Computing | 2024年 / 25卷 / 03期
关键词：
Deep belief network; Deep Boltzmann machine network; Deep learning; Text classification;
D O I：
10.12694/SCPE.V25I3.2742
中图分类号：
学科分类号：
摘要：
At present, the commonly used Bag of Words (BOW) expression ignores the semantic information of text and the problems of high dimension and high sparsity of feature extraction. This paper presents a multi-class text representation and classification algorithm. This project is based on the vector expression of keywords and takes the multi-category classification problem as the research object. Then, a hybrid Deep Location network (HDBN) is constructed by combining DBN with Boltzmann (DBM). Then, this paper does a lot of tests on the algorithm and proves the effectiveness of the algorithm. In addition, the 2D visual experiment is carried out with HDBN, and then the high-level text expression based on HDBN is obtained. The expression has strong cohesion and weak coupling. © 2024 SCPE.
引用
收藏
页码：1826 / 1832
页数：6
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