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The Effects of Gender Signals and Performance in Online Product Reviews

Sandipan Sikdar, Rachneet Sachdeva, Johannes Wachs, Johannes Wachs et al. • Frontiers in Big Data (2022)

This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdata.2021.771404

Does Emotional Labor Matter for University Teaching? Examining the Antecedents and Consequences of University Teachers' Emotional Labor Strategies

Jiying Han, Hongbiao Yin, Xin Yang, Feifei Wang • Frontiers in Psychology (2021)

Following Grandey's integrative model of emotional labor and emotion regulation, this study examined the relationships between university teachers' reported use of various emotional labor strategies and some antecedents (i. e., perceived em...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyg.2021.731099

Data Mining and Machine Learning

Mohammed Javeed Zaki, Wagner Meira • Cambridge University Press eBooks (2020)

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...

OPENALEX DOI: https://doi.org/10.1017/9781108564175

A Machine Learning-Oriented Survey on Tiny Machine Learning

Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access (2024)

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2024.3365349

Some results of the digital analysis of the semantic similarity of audiovisual translation texts (based on the films directed by Denis Villeneuve)

Aishat I. Lepshakova, Oleg V. Kurskikh • Актуальные проблемы филологии и педагогической лингвистики (2025)

The article analyses different translation versions of science fiction films directed by Denis Villeneuve with the aim of determining their semantic similarity through NLP analysis. There are four groups of metrics used in text analysis: se...

DOAJ Open Access (DOAJ) DOI: 10.29025/2079-6021-2025-1-132-150

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences (2024)

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrras.2024.101172

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19

Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports (2023)

Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-023-37592-1

A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome

Dong-Dong Wang, Ya-Feng Li, Yi-Zhen Mao, Su-Mei He et al. • Frontiers in Nutrition (2022)

The present study aimed to explore the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome (PCOS) and predict an appropriate dosage schedule using a machine-learning approach. Data were obtained fro...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnut.2022.851275

Machine Learning and Data Mining Methods in Diabetes Research

Ioannis Kavakiotis, O. Tsave, Athanasios Salifoglou, Nicos Maglaveras et al. • Computational and Structural Biotechnology Journal (2017)

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, ap...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.csbj.2016.12.005 PMC: 5257026

Introduction to Machine Learning

Richard J. Roiger • Chapman & Hall/CRC eBooks (2020)

R is one of the top-rated problem-solving tools for machine learning, data science, data analytics, data mining, and statistical analysis. R ’s popularity has resulted in the development of thousands of tutorials. Unfortunately, it’s easy t...

OPENALEX DOI: https://doi.org/10.1201/9781003006695-1

Machine learning unifies the modeling of materials and molecules

Albert P. Bartók, Sandip De, Carl R. Poelking, Noam Bernstein et al. • Science Advances (2017)

Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a...

OPENALEX cc-by-nc DOI: https://doi.org/10.1126/sciadv.1701816 PMC: 5729016

Human behavior analysis on political retweets using machine learning algorithms

Het Patel, Aditya Kansara, Boppuru Rudra Prathap, Kukatlapalli Pradeep Kumar • Measurement: Sensors (2023)

The exponential rise in the use of social media has resulted in a massive increase in the volume of unstructured text created. This content is presented through messages, conversations, postings, and blogs. Microblogging has become a popula...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.measen.2023.100768

Machine learning and its applications: A review

Sheena Angra, Sachin Ahuja • International Conference on Big Data Analytics and Computational Intelligence (ICBDAC) (2017)

Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data m...

OPENALEX DOI: https://doi.org/10.1109/icbdaci.2017.8070809

Machine Learning for Computational Heterogeneous Catalysis

Philomena Schlexer, Kirsten T. Winther, José Antonio Garrido Torres, Verena Streibel et al. • ChemCatChem (2019)

Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the developme...

OPENALEX DOI: https://doi.org/10.1002/cctc.201900595

DATA MINING AND MACHINE LEARNING IN ASTRONOMY

Nicholas M. Ball, Robert J. Brunner • International Journal of Modern Physics D (2010)

We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding ...

OPENALEX Open Access DOI: https://doi.org/10.1142/s0218271810017160

Machine learning in pain research

Jörn Lötsch, Alfred Ultsch • Pain (2017)

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1097/j.pain.0000000000001118 PMC: 5895117