Reset
Showing 20 of 3,812 academic articles

Natural language processing

Renáta Németh, Júlia Koltai • Intersections (2023)

Natural language processing (NLP) methods are designed to automatically process and analyze large amounts of textual data. The integration of this new-generation toolbox into sociology faces many challenges. NLP was institutionalized outsid...

OPENALEX cc-by DOI: https://doi.org/10.17356/ieejsp.v9i1.871

Natural Language Processing

Xavier Vasques • Wiley eBooks (2024)

This book chapter focuses on natural language processing (NLP) and covers various applications such as classifying messages as spam or ham, sentiment analysis, and the use of Bidirectional Encoder Representations from Transformers (BERT). T...

OPENALEX DOI: https://doi.org/10.1002/9781394220649.ch4

Forecasting student achievement in MOOCs with natural language processing

Carly D. Robinson, Michael Yeomans, Justin Reich, Chris S. Hulleman et al. • International Conference on Learning Analytics and Knowledge (LAK) (2016)

Student intention and motivation are among the strongest predictors of persistence and completion in Massive Open Online Courses (MOOCs), but these factors are typically measured through fixed-response items that constrain student expressio...

OPENALEX DOI: https://doi.org/10.1145/2883851.2883932

Natural Language Processing

Barry Walsh • Apress eBooks (2022)

Any book on operationalizing Artificial Intelligence today cannot ignore growth in Natural Language Processing (NLP), with market size projected to be $43b in 2025. Ostensibly the branch of AI concerned with programming computers to underst...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-8817-7_10

Suicide Note Classification Using Natural Language Processing: A Content Analysis

John P Pestian, Henry A. Nasrallah, Paweł Matykiewicz, Aurora J. Bennett et al. • Biomedical Informatics Insights (2010)

Suicide is the second leading cause of death among 25-34 year olds and the third leading cause of death among 15-25 year olds in the United States. In the Emergency Department, where suicidal patients often present, estimating the risk of r...

OPENALEX cc-by-nc DOI: https://doi.org/10.4137/bii.s4706 PMC: 3107011

Natural Language Processing

Santanu Pattanayak • Apress eBooks (2022)

In the modern age of information and analytics, natural language processing (NLP) is one of the most important technologies out there. Making sense of complex structures in language and deriving insights and actions from it are crucial from...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-8931-0_4

Impact of Machine Learning in Natural Language Processing: A Review

Tatwadarshi P. Nagarhalli, Vinod Moreshwar Vaze, Nirav Pravinsinh Rana • International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV) (2021)

The recent times have seen unprecedented growth in research and development in the field of Artificial Intelligence and its allied fields, subfields, like Machine Learning, Deep Learning and Natural Language Processing. The new found excite...

OPENALEX DOI: https://doi.org/10.1109/icicv50876.2021.9388380

Using natural language processing technology for qualitative data analysis

Kevin Crowston, Eileen E. Allen, Robert Heckman • International Journal of Social Research Methodology (2011)

Social researchers often apply qualitative research methods to study groups and their communications artifacts. The use of computer-mediated communications has dramatically increased the volume of text available, but coding such text requir...

OPENALEX DOI: https://doi.org/10.1080/13645579.2011.625764

A survey of uncertainty in deep neural networks

Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jong‐Seok Lee et al. • Artificial Intelligence Review (2023)

Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...

OPENALEX cc-by DOI: https://doi.org/10.1007/s10462-023-10562-9

Neural Networks in Structural Engineering

R. Daniel VanLuchene, ROUFEI SUN • Computer-Aided Civil and Infrastructure Engineering (1990)

In the past few years literature on computational civil engineering has concentrated primarily on artificial intelligence (Al) applications involving expert system technology. This article discusses a different Al approach involving neural ...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1111/j.1467-8667.1990.tb00377.x

A renaissance of neural networks in drug discovery

Igor I. Baskin, David Alan Winkler, Igor V. Tetko • Expert Opinion on Drug Discovery (2016)

INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...

OPENALEX DOI: https://doi.org/10.1080/17460441.2016.1201262

A neural-network-based detection of epilepsy

Vivek Prakash Nigam, Daniel Graupe • Neurological Research (2004)

Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced ne...

OPENALEX DOI: https://doi.org/10.1179/016164104773026534

On the Spectral Bias of Neural Networks

Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler et al. • arXiv (Cornell University) (2018)

Neural networks are known to be a class of highly expressive functions able to fit even random input-output mappings with $100\%$ accuracy. In this work, we present properties of neural networks that complement this aspect of expressivity. ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1806.08734

Neural networks in ocean engineering

Pooja Jain, Makarand Chintamani Deo • Ships and Offshore Structures (2005)

The soft computing technique of neural network is being extensively used across all disciplines of ocean engineering, namely, offshore, coastal, and deep-ocean engineering including marine engineering. This paper takes a stock of the resear...

OPENALEX DOI: https://doi.org/10.1533/saos.2004.0005

Neural networks in process fault diagnosis

T. Sorsa, Heikki N. Koivo, Hannu J. Koivisto • IEEE Transactions on Systems Man and Cybernetics (1991)

Fault detection and diagnosis is an important problem in process automation. Both model-based methods and expert systems have been suggested to solve the problem, along with the pattern recognition approach. A number of possible neural netw...

OPENALEX DOI: https://doi.org/10.1109/21.108299

State-of-the-art in artificial neural network applications: A survey

Oludare Isaac Abiodun, Aman Jantan, Abiodun Esther Omolara, Kemi Victoria Dada et al. • Heliyon (2018)

This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and ar...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.heliyon.2018.e00938 PMC: 6260436

iNNvestigate neural networks!

Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele et al. • arXiv (Cornell University) (2018)

In recent years, deep neural networks have revolutionized many application domains of machine learning and are key components of many critical decision or predictive processes. Therefore, it is crucial that domain specialists can understand...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1808.04260