Academic Articles & Research Papers

Natural language processing: state of the art, current trends and challenges

Natural Language Processing in Medicine: An Overview

An overview is given of natural language processing applications in medicine. An attempt has been made to enumerate the most important and known international projects and to summarize their goals, principles, methods and results. A section...

Deep learning for natural language processing: advantages and challenges

Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...

Natural Language Processing of Semitic Languages

Natural Language Processing Recipes

Implement natural language processing applications with Python in this problem-solution book. Here, coding exercises will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identi...

Five sources of bias in natural language processing

Recently, there has been an increased interest in demographically grounded bias in natural language processing (NLP) applications. Much of the recent work has focused on describing bias and providing an overview of bias in a larger context....

Historical Models and Serial Sources

Serial sources such as records, registers, and inventories are the ‘classic’ sources for quantitative history. Unstructured, narrative texts such as newspaper articles or reports were out of reach for historical analyses, both for practical...

ILSA: an automated language complexity analysis tool for French

Estimating language complexity is an important aspect of educational measurement and assessment that can be used, for instance, to control for unwanted variance due to language, or to provide students with texts that are conducive to learni...

Specialized Large Language Model for Standardization of Locomotive Maintenance Data

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...

Natural Language Processing in Radiology: A Systematic Review

Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology repo...

Natural Language Processing for Smart Healthcare

Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural ...

Foundations of statistical natural language processing

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains al...

Arabic Natural Language Processing

The Arabic language presents researchers and developers of natural language processing (NLP) applications for Arabic text and speech with serious challenges. The purpose of this article is to describe some of these challenges and to present...

<i>Computing Attitude and Affect in Text: Theory and Applications</i> James G. Shanahan, Yan Qu, and Janyce Wiebe (editors) (Clairvoyance Corporation and University of Pittsburgh) Dordrecht: Springer (The information retrieval series, edited by W. Bruce Croft), 2006, xv+341 pp; hardbound, ISBN 1-4020-4026-1, $99.00, €74.95

Exploring Scientific Outputs about Globalization: A Conceptual Framework Study

IntroductionBibliometric analysis is widely acknowledged as a robust and systematic approach for examining extensive scholarly literature. It serves as a vital tool for mapping the landscape of contemporary research across various academic ...

Assessing GPT's capabilities in consumer food survey analysis: A comparative approach for understanding food technophobia and novel protein perceptions

This study explores the application of GPT models for automating consumer food survey analysis, focusing on Chinese consumers' acceptance of plant-based foods, cultured meat, insect-based proteins, and microbial proteins. Traditional survey...

Natural Language Processing for Requirements Engineering

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...

Natural Language Processing

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

Natural Language Processing in Oncology

IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest im...

Natural language processing

Previous ARIST chapters (Haas, 1996;Warner, 1987) described a number of theoretical developments that have influenced research in NLP.The most recent theoretical developments can be grouped into four classes: (i) statistical and corpus-base...