Academic Articles & Research Papers

Distribution and resistance-associated genomic features of Acinetobacter in an urban wastewater network.

Framework for evaluating code generation ability of large language models

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and int...

Natural Language Processing-Based Financial Time Series Forecasting: Utilizing Sentiment Analysis for Improved Stock Price Prediction

This study explores the application of natural language processing (NLP) techniques in financial time series forecasting, specifically in predicting stock prices. Historical stock price data and textual data from financial news articles and...

Explainable hybrid deep learning framework for air quality index prediction in Indian cities

Abstract Air pollution constitutes one of the most pressing environmental and public health crises of the twenty-first century, disproportionately affecting rapidly urbanising nations such as India. Accurate prediction of the Air Quality In...

Caps Captioning: A Modern Image Captioning Approach Based on Improved Capsule Network

In image captioning models, the main challenge in describing an image is identifying all the objects by precisely considering the relationships between the objects and producing various captions. Over the past few years, many methods have b...

A Review of Natural Language Processing in Medical Education

Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical...

Natural Language Processing

Natural language processing is widely discussed and researched topic nowadays.As it is one of the oldest areas of research in machine leaning it is used in major fields such as machine translation speech recognition and text processing.Natu...

Natural Language Processing of Social Media as Screening for Suicide Risk

Suicide is among the 10 most common causes of death, as assessed by the World Health Organization. For every death by suicide, an estimated 138 people's lives are meaningfully affected, and almost any other statistic around suicide deaths i...

Evaluation of natural language processors

Despite a large amount of research on developing natural language understanding programs, little work has been done on evaluating their performance or potential. The evaluations that have been done have been unsystematic and incomplete. Thi...

Politeness research: Key trajectories and their applicability in intercultural communication

With the plethora of studies on politeness in general and linguistic politeness in particular, it is difficult for those who want to apply the theoretical findings to authentic language data, to find a roadmap to theoretical framework on wh...

Special Thematic Section on Semantic Models for Natural Language Processing (Preface)

With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Pr...

Ensembles machine learning for short duration rainfall intensity forecasting

Abstract This study introduces an ensemble machine learning (EML) framework to enhance short-duration rainfall-intensity prediction under limited-data conditions. By integrating multiple base learners within a stacking architecture, the pro...

Empowering text classification with NLP and explainable AI for enhanced interpretability

Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...

Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages

Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the mo...

Content Analysis of Medical Research Articles: A corpus-based study

Introduction: Content analysis applied for comparing texts, a writer’s works with others or the same author, the texts written in a natural language with texts in other languages literature and review of specialized field. The present study...

Weighted DAG Automata for Semantic Graphs

Graphs have a variety of uses in natural language processing, particularly as representations of linguistic meaning. A deficit in this area of research is a formal framework for creating, combining, and using models involving graphs that pa...

Challenges in Natural Language Processing

Although natural language processing has come far, the technology has not achieved a major impact on society. Is this because of some fundamental limitation that cannot be overcome? Or because there has not been enough time to refine and ap...

Comparative Study of CNN and RNN for Natural Language Processing

Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main types of DNN architectures, are widely explored to handle var...

Natural Language Processing

Natural language processing is a fast-evolving field with popular applications in language translation, speech recognition, text classification, and summarization of text, among others. The central aspect of NLP is vectorizing text data. Te...

Fraud detection with natural language processing

Abstract Automated fraud detection can assist organisations to safeguard user accounts, a task that is very challenging due to the great sparsity of known fraud transactions. Many approaches in the literature focus on credit card fraud and ...