|
A Survey of Long Short Term Memory (LSTM) a Lgorithm and its Application
|
| |
|
|
|
Abstract: (1339 Views) |
| Recursive neural networks are a model of deep learning techniques that has been a very popular topic for the past few decades. LSTM neural networks are a new way of processing information that, because of its chain structure, operates on time-series data that leads to powerful deep learning events if LSTM is an important feature in the input sequence. Recognize in the early stages because of its short-term memory, it can transmit this information over long distances and receive and maintain such potential long-term dependencies. In this article, we have tried to examine the types of LSTM and their application in text processing in the fields of text classification, emotion analysis and feature extraction. In addition, we have also considered identifying future goals and highlighting the path of future research |
|
| Keywords: : Deep learning, Recurrent neural network LSTM, Natural language processing, Feature extraction |
|
|
Full-Text [PDF 5802 kb]
(412 Downloads)
|
Type of Study: Scientific-extension |
Subject:
Special
Received: 2021/08/2 | Accepted: 2021/08/1 | Published: 2021/08/1
|
|
|
|
|
|
