AIMC Topic: Language

Clear Filters Showing 981 to 990 of 1580 articles

RTJTN: Relational Triplet Joint Tagging Network for Joint Entity and Relation Extraction.

Computational intelligence and neuroscience
Extracting entities and relations from unstructured sentences is one of the most concerned tasks in the field of natural language processing. However, most existing works process entity and relation information in a certain order and suffer from the ...

Chinese Language Feature Analysis Based on Multilayer Self-Organizing Neural Network and Data Mining Techniques.

Computational intelligence and neuroscience
As one of the oldest languages in the world, Chinese has a long cultural history and unique language charm. The multilayer self-organizing neural network and data mining techniques have been widely used and can achieve high-precision prediction in di...

The simulation experiment description markup language (SED-ML): language specification for level 1 version 4.

Journal of integrative bioinformatics
Computational simulation experiments increasingly inform modern biological research, and bring with them the need to provide ways to annotate, archive, share and reproduce the experiments performed. These simulations increasingly require extensive co...

A language modeling-like approach to sketching.

Neural networks : the official journal of the International Neural Network Society
Sketching is a universal communication tool that, despite its simplicity, is able to efficiently express a large variety of concepts and, in some limited contexts, it can be even more immediate and effective than natural language. In this paper we ex...

A disease-specific language representation model for cerebrovascular disease research.

Computer methods and programs in biomedicine
BACKGROUND: Effectively utilizing disease-relevant text information from unstructured clinical notes for medical research presents many challenges. BERT (Bidirectional Encoder Representation from Transformers) related models such as BioBERT and Clini...

Unsupervised cross-lingual model transfer for named entity recognition with contextualized word representations.

PloS one
Named entity recognition (NER) is one fundamental task in the natural language processing (NLP) community. Supervised neural network models based on contextualized word representations can achieve highly-competitive performance, which requires a larg...

Spoken Language Identification Using Deep Learning.

Computational intelligence and neuroscience
The process of detecting language from an audio clip by an unknown speaker, regardless of gender, manner of speaking, and distinct age speaker, is defined as spoken language identification (SLID). The considerable task is to recognize the features th...

Emotion Correlation Mining Through Deep Learning Models on Natural Language Text.

IEEE transactions on cybernetics
Emotion analysis has been attracting researchers' attention. Most previous works in the artificial-intelligence field focus on recognizing emotion rather than mining the reason why emotions are not or wrongly recognized. The correlation among emotion...

BERTtoCNN: Similarity-preserving enhanced knowledge distillation for stance detection.

PloS one
In recent years, text sentiment analysis has attracted wide attention, and promoted the rise and development of stance detection research. The purpose of stance detection is to determine the author's stance (favor or against) towards a specific targe...

Dual coding of knowledge in the human brain.

Trends in cognitive sciences
How does the human brain code knowledge about the world? While disciplines such as artificial intelligence represent world knowledge based on human language, neurocognitive models of knowledge have been dominated by sensory embodiment, in which knowl...