AIMC Topic: Language

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SG-Net: Syntax Guided Transformer for Language Representation.

IEEE transactions on pattern analysis and machine intelligence
Understanding human language is one of the key themes of artificial intelligence. For language representation, the capacity of effectively modeling the linguistic knowledge from the detail-riddled and lengthy texts and getting ride of the noises is e...

An Improved BERT and Syntactic Dependency Representation Model for Sentiment Analysis.

Computational intelligence and neuroscience
Text representation of social media is an important task for users' sentiment analysis. Utilizing the better representation, we can accurately acquire the real semantic information expressed by online users. However, existing works cannot achieve the...

Research on Feature Extraction and Chinese Translation Method of Internet-of-Things English Terminology.

Computational intelligence and neuroscience
Feature extraction and Chinese translation of Internet-of-Things English terms are the basis of many natural language processing. Its main purpose is to extract rich semantic information from unstructured texts to allow computers to further calculate...

An Entity Relationship Extraction Model Based on BERT-BLSTM-CRF for Food Safety Domain.

Computational intelligence and neuroscience
Dealing with food safety issues in time through online public opinion incidents can reduce the impact of incidents and protect human health effectively. Therefore, by the smart technology of extracting the entity relationship of public opinion events...

English Teaching Quality Monitoring and Multidimensional Analysis Based on the Internet of Things and Deep Learning Model.

Computational intelligence and neuroscience
With the development of the times, English as the universal language in the world has been highly valued by the society and schools, and English skills have become a basic skill in the society. The school is actively developing, and in the process of...

LM-GVP: an extensible sequence and structure informed deep learning framework for protein property prediction.

Scientific reports
Proteins perform many essential functions in biological systems and can be successfully developed as bio-therapeutics. It is invaluable to be able to predict their properties based on a proposed sequence and structure. In this study, we developed a n...

Multilabel classification of medical concepts for patient clinical profile identification.

Artificial intelligence in medicine
BACKGROUND: The development of electronic health records has provided a large volume of unstructured biomedical information. Extracting patient characteristics from these data has become a major challenge, especially in languages other than English.

Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT.

BMC bioinformatics
BACKGROUND: The abundance of biomedical text data coupled with advances in natural language processing (NLP) is resulting in novel biomedical NLP (BioNLP) applications. These NLP applications, or tasks, are reliant on the availability of domain-speci...

Optimization of English Machine Translation by Deep Neural Network under Artificial Intelligence.

Computational intelligence and neuroscience
To improve the function of machine translation to adapt to global language translation, the work takes deep neural network (DNN) as the basic theory, carries out transfer learning and neural network translation modeling, and optimizes the word alignm...

Association between loneliness and acceptance of using robots and pets as companions among older Chinese immigrants during the COVID-19 pandemic.

Australasian journal on ageing
OBJECTIVES: To examine loneliness experienced by middle-aged and older Chinese immigrants and its association with accepting technology as a companion (apps, Internet and robots) versus owning pets, when social distancing measures were implemented in...