WTL-CNN: a news text classification method of convolutional neural network based on weighted word embedding

• Published in: Connection science Vol. 34; no. 1; pp. 2291 - 2312
• Main Authors: Zhao, Weidong, Zhu, Lin, Wang, Ming, Zhang, Xiliang, Zhang, Jinming
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 31.12.2022; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Accuracy; Algorithms; Artificial neural networks; Classification; Embedding; LDA; Neural networks; News; News text classification; pooling layer; Text categorization; TF-IDF; topic information; Word2vec

The word embedding model word2vec tends to ignore the importance of a single word to the entire document, which affects the accuracy of the news text classification method. To address this problem, a method that combines word2vec, a topic-based TF-IDF algorithm, and an improved convolutional neural...