Firstly, according to the differences in methods, we divided the deep learning text retrieval model into four categories: DNN-based, CNN-based, RNN-based, and ...
This review is expected to provide basic Nnowledge and effective research entry points for scholars engaged in deep learning text retrieval. Keywords: Deep ...
We investigate the use of multimodal information contained in images as an effective method for enhancing the commonsense of Transformer models for text ...
Aug 10, 2023 · The purpose of this research is to explore the performance of deep learning networks and deep transformer models in review-based recommender systems.
Oct 20, 2023 · While CNNs were likely inferior to RNNs on a modeling basis, the fact that they could train substantially faster made them the preferred model.
Missing: DNN, | Show results with:DNN,
Deep Text Retrieval Models based on DNN, CNN, RNN and Transformer: A review · Injecting the BM25 Score as Text Improves BERT-Based Re-rankers · Axiomatically ...
A deep learning-based method for sentence queries, called DeepSenSe, is developed using citation data available in full-text articles obtained from PubMed ...
The state-of-the-art solutions to the vocabulary mismatch in information retrieval (IR) mainly aim at leveraging either the relational semantics provided by ...
Aug 15, 2024 · This article aims to present an encompassing survey that focuses on CNNs and the evolution of RNNs to ViTs given their importance in the domain of HAR.
Missing: DNN, | Show results with:DNN,
Deep learning–based models have surpassed classical machine learning–based approaches in various text classification tasks, including sentiment analysis, ...