[HTML][HTML] Neural machine translation: A review of methods, resources, and tools
Abstract Machine translation (MT) is an important sub-field of natural language processing
that aims to translate natural languages using computers. In recent years, end-to-end neural …
that aims to translate natural languages using computers. In recent years, end-to-end neural …
Senti‐eSystem: a sentiment‐based eSystem‐using hybridized fuzzy and deep neural network for measuring customer satisfaction
In the competing era of online industries, understanding customer feedback and satisfaction
is one of the important concern for any business organization. The well‐known social media …
is one of the important concern for any business organization. The well‐known social media …
A novel LSTM-GAN algorithm for time series anomaly detection
G Zhu, H Zhao, H Liu, H Sun - 2019 prognostics and system …, 2019 - ieeexplore.ieee.org
Time series anomaly detection is an important part of Prognostic and Health Management
(PHM), and has been widely studied and followed with interest. The data with time series …
(PHM), and has been widely studied and followed with interest. The data with time series …
A Survey on Machine Translation of Low-Resource Arabic Dialects
For many years, machine translation has been one of the most studied topics for AI
researchers, this initially started with simple and traditional approaches like statistical …
researchers, this initially started with simple and traditional approaches like statistical …
A reverse positional encoding multi-head attention-based neural machine translation model for arabic dialects
Languages with a grammatical structure that have a free order for words, such as Arabic
dialects, are considered a challenge for neural machine translation (NMT) models because …
dialects, are considered a challenge for neural machine translation (NMT) models because …
A transformer-based neural machine translation model for Arabic dialects that utilizes subword units
Languages that allow free word order, such as Arabic dialects, are of significant difficulty for
neural machine translation (NMT) because of many scarce words and the inefficiency of …
neural machine translation (NMT) because of many scarce words and the inefficiency of …
Transformer Text Classification Model for Arabic Dialects That Utilizes Inductive Transfer
In the realm of the five-category classification endeavor, there has been limited exploration
of applied techniques for classifying Arabic text. These methods have primarily leaned on …
of applied techniques for classifying Arabic text. These methods have primarily leaned on …
Multitasking learning model based on hierarchical attention network for Arabic sentiment analysis classification
Limited approaches have been applied to Arabic sentiment analysis for a five-point
classification problem. These approaches are based on single task learning with a …
classification problem. These approaches are based on single task learning with a …
A dilated convolution network-based LSTM model for multi-step prediction of chaotic time series
R Wang, C Peng, J Gao, Z Gao, H Jiang - Computational and Applied …, 2020 - Springer
Aiming to solve the problems of low accuracy of multi-step prediction and difficulty in
determining the maximum number of prediction steps of chaotic time series, a multi-step time …
determining the maximum number of prediction steps of chaotic time series, a multi-step time …
Toward fluent Arabic poem generation based on fine-tuning AraGPT2 transformer
O Abboushi, M Azzeh - Arabian Journal for Science and Engineering, 2023 - Springer
Arabic poetry is delicate literature that requires simultaneously adhering to a specific meter
and rhyme. These restrictions make the computer unable to compose poems correctly. In the …
and rhyme. These restrictions make the computer unable to compose poems correctly. In the …