Abstract

The categorization of Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and Convolutional Recurrent Neural Networks (CRNNs) for use in document retrieval are thoroughly discussed in this review paper. By analyzing and summarizing the conclusions from over forty studies that relate to the individual models’ efficacy, the study offers a comprehensive assessment of the individual models’ performance. It explores the potential outcomes of the group strategies in enhancing document retrieval accuracy.