Academic Articles & Research Papers

Decolonizing Algorithms: AI-Driven Media and the Reclamation of African Linguistic Identities

This study examines the influence of artificial intelligence (AI)-driven media platforms on South Africa's indigenous languages—Setswana, Tshivenda, and Xitsonga—in the country's diverse linguistic environment. It examines how algorithmic b...

Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand?

AbstractLanguage models trained on billions of tokens have recently led to unprecedented results on many NLP tasks. This success raises the question of whether, in principle, a system can ever “understand” raw text without access to some fo...

Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed

BackgroundNatural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and incr...

Improving Web Readability Using Video Content: A Relevance-Based Approach

With the increasing integration of multimedia elements into webpages, videos have emerged as a popular medium for enhancing user engagement and knowledge retention. However, irrelevant or poorly placed videos can hinder readability and dist...

Natural Language Processing and Information Retrieval

Natural Language Processing and Information Retrieval is a textbook designed to meet the requirements of engineering students pursuing undergraduate and postgraduate programs in computer science and information technology. The book attempts...

Natural language processing

Article Free Access Share on Natural language processing: what's really involved? Authors: Roger Schank Yale University, New Haven, CT Yale University, New Haven, CTView Profile , Alex Kass Yale University, New Haven, CT Yale University, Ne...

Natural language processing for prolog programmers

Natural language processing: A review

Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing - EMNLP '06

We are delighted to introduce the proceedings of the 11th Conference on Empirical Methods in Natural Language Processing, organized under the auspices of SIGDAT, the ACL Special Interest Group for linguistic data and corpus-based approaches...

MedScan, a natural language processing engine for MEDLINE abstracts

MOTIVATION: The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely us...

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...

A linguistic ontology of space for natural language processing

Lexical Functions in Lexicography and Natural Language Processing

Lexical Functions in Lexicography and Natural Language Processing is entirely devoted to the topic of Lexical Functions, which have been introduced in the framework of the Meaning-Text Theory (MTT) as a means for describing restricted lexic...

Natural Language Processing

From the Publisher: These ten contributions describe the major technical ideas underlying many of the significant advances in natural language processing over the last decade, focusing in particular on the challenges in areas such as knowl...

Natural Language Processing (NLP): An Introduction

Natural language processing in-and-for design research

Abstract We review the scholarly contributions that utilise natural language processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period...

Data augmentation techniques in natural language processing

Data Augmentation (DA) methods – a family of techniques designed for synthetic generation of training data – have shown remarkable results in various Deep Learning and Machine Learning tasks. Despite its widespread and successful adoption w...

Natural Language Processing, Sentiment Analysis, and Clinical Analytics

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

Information Extraction From FDA Drug Labeling to Enhance Product-Specific Guidance Assessment Using Natural Language Processing

Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and ...