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Application of LSTM Neural Network Technology Embedded in English Intelligent Translation.

Computational intelligence and neuroscience
With the rapid development of computer technology, the loss of long-distance information in the transmission process is a prominent problem faced by English machine translation. The self-attention mechanism is combined with convolutional neural netwo...

Study of Intelligent Wireless Network Management in the Context of Artificial Intelligence for the Improvement of Chinese Language Mandarin Test Training Programmes.

Computational intelligence and neuroscience
One of the most prominent ways of communication between people is through language, which plays a significant role in expressing thoughts. Different ways of expressing a language can be through speech, writing, signing, or gesture. Each country has t...

A Data-Driven Model for Automated Chinese Word Segmentation and POS Tagging.

Computational intelligence and neuroscience
Chinese natural language processing tasks often require the solution of Chinese word segmentation and POS tagging problems. Traditional Chinese word segmentation and POS tagging methods mainly use simple matching algorithms based on lexicons and rule...

Research and Implementation of Text Generation Based on Text Augmentation and Knowledge Understanding.

Computational intelligence and neuroscience
Text generation has always been limited by the lack of corpus data required for language model (LM) training and the low quality of the generated text. Researchers have proposed some solutions, but these solutions are often complex and will greatly i...

Machine-learning as a validated tool to characterize individual differences in free recall of naturalistic events.

Psychonomic bulletin & review
The use of naturalistic stimuli, such as narrative movies, is gaining popularity in many fields, characterizing memory, affect, and decision-making. Narrative recall paradigms are often used to capture the complexity and richness of memory for natura...

AFR-BERT: Attention-based mechanism feature relevance fusion multimodal sentiment analysis model.

PloS one
Multimodal sentiment analysis is an essential task in natural language processing which refers to the fact that machines can analyze and recognize emotions through logical reasoning and mathematical operations after learning multimodal emotional feat...

Multi-granularity heterogeneous graph attention networks for extractive document summarization.

Neural networks : the official journal of the International Neural Network Society
Extractive document summarization is a fundamental task in natural language processing (NLP). Recently, several Graph Neural Networks (GNNs) are proposed for this task. However, most existing GNN-based models can neither effectively encode semantic n...

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts.

Journal of medical Internet research
BACKGROUND: Dementia is a global public health priority due to rapid growth of the aging population. As China has the world's largest population with dementia, this debilitating disease has created tremendous challenges for older adults, family careg...

Artificial intelligence for topic modelling in Hindu philosophy: Mapping themes between the Upanishads and the Bhagavad Gita.

PloS one
The Upanishads are known as one of the oldest philosophical texts in the world that form the foundation of Hindu philosophy. The Bhagavad Gita is the core text of Hindu philosophy and is known as a text that summarises the key philosophies of the Upa...

Synthesizing theories of human language with Bayesian program induction.

Nature communications
Automated, data-driven construction and evaluation of scientific models and theories is a long-standing challenge in artificial intelligence. We present a framework for algorithmically synthesizing models of a basic part of human language: morpho-pho...