Academic Articles & Research Papers

Enhancing sentiment classification on small datasets through data augmentation and transfer learning

Abstract Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models. This study evaluates and compares the effectiveness of three data augmentation strategies: Easy Data Augm...

A Multi-Stage NLP Framework for Knowledge Discovery from Crop Disease Research Literature

Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...

Advancements in natural language processing: Implications, challenges, and future directions

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

Application of Convolutional Neural Network in Natural Language Processing

Convolutional neural network (Convolutionl Neural Network, CNN) is a multiple-layer neural network method to learn hierarchical characteristic of data. In recent years, CNN has developed rapidly in the design and calculation of natural lang...

Natural Language Processing

Natural language processing (NLP) refers to the field of study that focuses on the interactions between human language and computers. It is a computational approach to text analysis. It is the application of a wide range of computational te...

Natural Language Processing Technologies in Radiology Research and Clinical Applications

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. How...

Applications of natural language processing and large language models in materials discovery

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

Python Natural Language Processing

Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...

A Study on Instructional Humor: How Much Humor Is Used in Presentations?

Humor is applied in pedagogy to create a positive learning environment. Recent research focuses on the theories, effects, individual differences, and qualitative aspects of humor for instruction. However, there is a lack of studies focusing...

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...

Natural Language Processing for Online Applications

Technology practitioners in the Internet space are constantly faced with difficult decision-making as to what research has been done and what the best practices are. This lucid text covers the emerging technologies of document retrieval, in...

Evolution of transfer learning in natural language processing

In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...

A systematic review of natural language processing applied to radiology reports

BACKGROUND: Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to r...

Natural Language Processing for Policymaking

Abstract Language is the medium for many political activities, from campaigns to news reports. Natural language processing (NLP) uses computational tools to parse text into key information that is needed for policymaking. In this chapter, w...

TweetNLP: Cutting-Edge Natural Language Processing for Social Media

Jose Camacho-collados, Kiamehr Rezaee, Talayeh Riahi, Asahi Ushio, Daniel Loureiro, Dimosthenis Antypas, Joanne Boisson, Luis Espinosa Anke, Fangyu Liu, Eugenio Martínez Cámara. Proceedings of the 2022 Conference on Empirical Methods in Nat...

Natural Language Processing – IJCNLP 2005

A comparative empirical evaluation of semantic clustering algorithms on static word embeddings

Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

Sentiment Analysis and Topic Modeling of Indonesian Public Conversation about COVID-19 Epidemics on Twitter

The World Health Organization (WHO) declared the COVID-19 outbreak has resulted in more than six million confirmed cases and more than 371,000 deaths globally on June 1, 2020. The incident sparked a flood of scientific research to help soci...

Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models

Abstract To efficiently and accurately understand, detect, and treat sepsis, we require a deep understanding of how its underlying biological systems work. Conventional methods struggle to provide a detailed view of both the functional and ...