AIMC Topic: Language

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A BERT-Based Aspect-Level Sentiment Analysis Algorithm for Cross-Domain Text.

Computational intelligence and neuroscience
Cross-domain text sentiment analysis is a text sentiment classification task that uses the existing source domain annotation data to assist the target domain, which can not only reduce the workload of new domain data annotation, but also significantl...

Construction and Research on Chinese Semantic Mapping Based on Linguistic Features and Sparse Self-Learning Neural Networks.

Computational intelligence and neuroscience
In this paper, we adopt the algorithms of linguistic feature Rong and sparse self-learning neural network to conduct an in-depth study and analysis of Chinese semantic mapping, which complements the emotion semantic representation ability of traditio...

Knowledge Graph-Enabled Text-Based Automatic Personality Prediction.

Computational intelligence and neuroscience
How people think, feel, and behave primarily is a representation of their personality characteristics. By being conscious of the personality characteristics of individuals whom we are dealing with or deciding to deal with, one can competently amelior...

Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition.

Sensors (Basel, Switzerland)
Sign language is the main channel for hearing-impaired people to communicate with others. It is a visual language that conveys highly structured components of manual and non-manual parameters such that it needs a lot of effort to master by hearing pe...

Improving the robustness and accuracy of biomedical language models through adversarial training.

Journal of biomedical informatics
Deep transformer neural network models have improved the predictive accuracy of intelligent text processing systems in the biomedical domain. They have obtained state-of-the-art performance scores on a wide variety of biomedical and clinical Natural ...

Character gated recurrent neural networks for Arabic sentiment analysis.

Scientific reports
Sentiment analysis is a Natural Language Processing (NLP) task concerned with opinions, attitudes, emotions, and feelings. It applies NLP techniques for identifying and detecting personal information from opinionated text. Sentiment analysis deduces ...

Adoption of Wireless Network and Artificial Intelligence Algorithm in Chinese-English Tense Translation.

Computational intelligence and neuroscience
In order to solve the problem of tense consistency in Chinese-English neural machine translation (NMT) system, a Chinese verb tense annotation model is proposed. Firstly, a neural network is used to build a Chinese tense annotation model. During the ...

Enhancing Text Generation via Parse Tree Embedding.

Computational intelligence and neuroscience
Natural language generation (NLG) is a core component of machine translation, dialogue systems, speech recognition, summarization, and so forth. The existing text generation methods tend to be based on recurrent neural language models (NLMs), which g...

Personalized College English Learning Based on Deep Learning under the Background of Big Data.

Computational intelligence and neuroscience
Generally, in-depth learning has been extensively employed in numerous industries to enhance the growth of economic globalization since the dawn of the big data age. At the same time, the demand for foreign language talent has risen dramatically, and...

Language models can learn complex molecular distributions.

Nature communications
Deep generative models of molecules have grown immensely in popularity, trained on relevant datasets, these models are used to search through chemical space. The downstream utility of generative models for the inverse design of novel functional compo...