Deep learning--based models have surpassed classical machine learning--based
approaches in various text classification tasks, including sentiment analysis, news …

Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …

This study presents a computationally efficient deep learning model for binary sentiment
classification, which aims to decide the sentiment polarity of people's opinions, attitudes, and …

In regions of visual inference, optimized performance is demonstrated by capsule networks
on structured data. Classification of hierarchical multi-label text is performed with a simple …

In recent years, many applications are using various forms of deep learning models. Such
methods are usually based on traditional learning paradigms requiring the consistency of …

Aspect-based (aspect-level) sentiment analysis is an important task in fine-grained
sentiment analysis, which aims to automatically infer the sentiment towards an aspect in its …

Scholarly venue recommendation is an emerging field due to a rapid surge in the number of
scholarly venues concomitant with exponential growth in interdisciplinary research and …

Spatio-temporal wind speed prediction is of great significance to the grid-connected
operation of multiple wind farms in smart grid. This paper proposes a spatio-temporal wind …

Text classification is a popular research topic in the field of natural language processing and
provides wide applications. The existing text classification methods based on deep neural …

Investigating public attitudes on social media is important in opinion mining systems. Stance
detection aims to analyze the attitude of an opinionated text (eg, favor, neutral, or against) …