Academic Articles & Research Papers

Natural Language Processing

ABSTRACT: Language is way of communicating your words Language helps in understanding the world,we get a better insight of the world. Language helps speakers to be as vague or as precise as they like. NLP Stands for natural language process...

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...

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.

information)...

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...

SSAM: a span spatial attention model for recognizing named entities

Abstract Mapping a sentence into a two-dimensional (2D) representation can flatten nested semantic structures and build multi-granular span dependencies in named entity recognition. Existing approaches to recognizing named entities often cl...

<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 ...

Transfer Learning in Natural Language Processing

The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...

Handbook of Natural Language Processing

Symbolic approaches to natural language processing tokenisation and sentence segmentation lexical analysis parsing techniques semantic analysis discourse structure and intention recognition natural language generation intelligent writing as...

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...

Attention in Natural Language Processing

Attention is an increasingly popular mechanism used in a wide range of neural architectures. The mechanism itself has been realized in a variety of formats. However, because of the fast-paced advances in this domain, a systematic overview o...

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...

Advances in natural language processing

Natural language processing employs computational techniques for the purpose of learning, understanding, and producing human language content. Early computational approaches to language research focused on automating the analysis of the lin...

Natural language processing: an introduction

OBJECTIVES: To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. TARGET AUDIENCE: This tutorial targets the medical informatics generalist who has limited acquaintance with the principles be...

Natural language processing with Python

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'...

Collectively encoding protein properties enriches protein language models

Abstract Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such p...

La focalisation des conditionnelles

The aim of this article is to identify the different syntactic modes existing in French to focus if-clauses in constructions such as {if-P, Q}, and {Q if-P}. It is not irrelevant to consider that if-clauses may occupy a focus position, seei...