Название: System Innovation for a Troubled World: Applied System Innovation
Автор: Artde Donald Kin-Tak Lam, Stephen D. Prior, Siu-Tsen Shen
Издательство: CRC Press
Серия: Smart Science, Design and Technology
Год: 2023
Страниц: 179
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
The major themes on technology included Material Science & Engineering, Communication Science & Engineering, Computer Science & Engineering, Electrical & Electronic Engineering, Mechanical & Automation Engineering, Architecture Engineering, IOT Technology, and Innovation Design. Sentiment analysis of text data is an important task in natural language processing (NLP). Taking the product review system as an example, proper use of sentiment analysis can reveal the opinions of consumers, and thus adjustments can be made to products. However, most current sentiment analysis methods assume that there is a large amount of training data available for the classification model. The classification accuracy is not ideal when little data are available for analysis.Aiming at sentiment analysis of text data with few data samples, in this paper, we propose an embedded learning model, which combines convolutional neural network and bidirectional long short-term memory learning models to improve the relevance of data by dimensionality reduction and thus strengthen the classification accuracy of few-shot learning. In addition, we segment the training data and use them to train the proposed model in batches to avoid the overfitting problem that is often observed in few-shot learning models.