AIMC Topic: Language

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Modeling Trajectories Obtained from External Sensors for Location Prediction via NLP Approaches.

Sensors (Basel, Switzerland)
Representation learning seeks to extract useful and low-dimensional attributes from complex and high-dimensional data. Natural language processing (NLP) was used to investigate the representation learning models to extract words' feature vectors usin...

PICO entity extraction for preclinical animal literature.

Systematic reviews
BACKGROUND: Natural language processing could assist multiple tasks in systematic reviews to reduce workflow, including the extraction of PICO elements such as study populations, interventions, comparators and outcomes. The PICO framework provides a ...

Construction and Computation of the College English Teaching Path in the Artificial Intelligence Teaching Environment.

Computational intelligence and neuroscience
Today, English is the world's main international language and is widely spoken. In this context, the learning of English has long been valued by all countries. In addition, English plays an essential role in the process of economic globalization, spe...

Deep Learning-Based Classification of Spoken English Digits.

Computational intelligence and neuroscience
Classification of isolated digits is the basic challenge for many speech classification systems. While a lot of work has been carried out on spoken languages, only limited research work on spoken English digit data has been reported in the literature...

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...