Sentiment analysis can be used to derive knowledge that is connected to emotions and
opinions from textual data generated by people. As computer power has grown, and the …

Sentiment analysis is one of the sub-domains of Natural Language Processing (NLP) that is
of piqued interest in the research community. With the advent of e-commerce and social …

Sentiment analysis (SA) or emotion AI or opinion mining uses natural language processing
(NLP). Sentiment Analysis identify, study, quantify, obtain, tacit states and subject related …

A Transformer-based short-term landslide displacement prediction model is proposed by
combining temporal convolutional network (TCN) with a Transformer decoder. This model …

This study makes a significant progress in addressing the challenges of short-term slope
displacement prediction in the Universal Landslide Monitoring Program, an unprecedented …

Neural language models are becoming the prevailing methodology for the tasks of query
answering, text classification, disambiguation, completion and translation. Commonly …

Large pretrained language models using the transformer neural network architecture are
becoming a dominant methodology for many natural language processing tasks, such as …

Attention mechanism is now being widely used in machine translation, image segmentation,
and many other neural network-based applications. In the attention mechanism, there is an …

Aspect‐based sentiment analysis (ABSA) is a fine‐grained sentiment analysis technology. In
recent years, neural networks are widely used to extract features of aspects and contexts …

Natural language processing (NLP) task like machine translation, sentence summarization,
sentence pair modeling, paraphrase identification, natural language inference, question …