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ORCIDMachine Learning and Data Analytics for Solving Business Problems 2022
- Bader A. Alyoubi, Chiheb-Eddine Ben Ncir, Ibraheem Mubarak Alharbi, Anis Jarboui:
Machine Learning and Data Analytics for Solving Business Problems: Methods, Applications, and Case Studies. Unsupervised and Semi-Supervised Learning, Springer 2022, ISBN 978-3-031-18483-3 - Frank Eichinger
, Moritz Mayer:
Predicting Salaries with Random-Forest Regression. 1-21 - Chiheb-Eddine Ben Ncir, Bader A. Alyoubi, Roaa Alrazyeg:
Data-Driven Analysis of Microfinance and Social Loans Before and During the COVID-19 Pandemic Using Exploratory Analysis and Decision Tree Classifiers. 23-40 - Waad Bouaguel, Taghrid Al Silimani:
Identification of Credit Risks Using Cluster Analysis and Behavioural Scoring During the COVID-19 Pandemic. 41-54 - Chibuzor Udokwu, Patrick Brandtner, Farzaneh Darbanian, Taha Falatouri:
Improving Sales Prediction for Point-of-Sale Retail Using Machine Learning and Clustering. 55-73 - R. Jothi, K. Muthukumaran:
Telecom Customer Segmentation Using Deep Embedded Clustering Algorithm. 75-88 - Sonia Ouni, Karim Kamoun, Mohammad Alattas:
Semantic Image Quality Assessment Using Conventional Neural Network for E-Commerce Catalogue Management. 89-113 - Khedija Arour, Rim Dridi:
Contextual Recommender Systems in Business from Models to Experiments. 115-140 - Maha Fraj, Mohamed Aymen Ben HajKacem, Nadia Essoussi:
An Overview of Multi-View Methods for Text Clustering. 141-164 - Siwar Gorrab, Fahmi Ben Rejab, Kaouther Nouira:
Real-Time K-Prototypes for Incremental Attribute Learning Using Feature Selection. 165-187 - Taha M. Mohamed, Abdulaziz Alharbi, Ibrahim Alhassan, Sherif A. Kholeif:
Applications of Industry 4.0 on Saudi Supply Chain Management: Technologies, Opportunities, and Challenges. 189-204
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