The Future of Data Mining

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Cem Ufuk Baytar, PhD – University Lecturer, Management Information Systems, İstanbul Topkapı University, Istanbul, Turkey

Series: Research Methodology and Data Analysis
BISAC: COM018000; COM021030; COM094000
DOI: https://doi.org/10.52305/KCIN5931

The purpose of this book is to discuss data mining, which is a subset of data science, from a variety of perspectives. With the technological advances of recent years, new software and hardware-based systems are available in most business environments. With these systems, data production continues to increase in personal, corporate, commercial and many other areas. Information systems convert raw data, which alone are not so meaningful, into information after the processes are applied. Database systems are necessary for the storage and management of the information generated. Revealing meaningful relationships hidden in a stack of high-volume data shows the function of data mining. Processing big data has become important to produce information that will support business decisions and be a strategic tool in today’s competitive environment. In this context, the effectiveness of data mining applications is increasing day by day as a decision support system to develop marketing strategies in every sector by identifying customer behavior and target groups.

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Table of Contents

Preface

Chapter 1. Data Analytics Applied to the Human Resources Industry
Cem Ufuk Baytar
Management Information Systems, Istanbul Topkapı University, Istanbul, Turkey

Chapter 2. Toxicogenomics Data Mining as a Promising Prioritization Tool in Toxicity Testing
Katarina Živančević¹,², Dragica Bozic¹, Katarina Baralić¹ and Danijela Đukić-Ćosić¹
¹Department of Toxicology “Akademik Danilo Soldatović,” University of Belgrade – Faculty of Pharmacy, Belgrade, Serbia
²Institute of Physiology and Biochemistry “Ivan Đaja,” University of Belgrade – Faculty of Biology, Belgrade, Serbia

Chapter 3. Applications of Data Mining Algorithms for Customer Recommendations in Retail Marketing
Elif Delice¹, Lütviye Özge Polatlı², İrem Düzdar Argun³, and Hakan Tozan4
¹Management Information Systems, Istanbul Topkapı University, Istanbul, Turkey
²Healthcare Systems Engineering, Istanbul Medipol University, Istanbul, Turkey
³Industrial Engineering, Düzce University, Düzce, Turkey
4Industrial Engineering, Istanbul Medipol University, Istanbul, Turkey

Chapter 4. Analysis of Customer Churn in the Banking Industry Using Data Mining
Özge Doğuç
Management Information Systems, Medipol University, Istanbul, Turkey

Chapter 5. The Crowdsourcing Concept-Based Data Mining Approach Applied in Prosumer Microgrids
B. C. Neagu, PhD, M. Gavrilaș, PhD, O. Ivanov, PhD and G. Grigoraș
Department of Power Engineering, “Gheorghe Asachi” Technical University, Iasi, Romania

Chapter 6. Active Learning
Jože M. Rožanec¹,²,³, Blaž Fortuna² and Dunja Mladenić¹
¹Laboratory of Artificial Intelligence, Jožef Stefan Institute, Ljubljana, Slovenia
²Qlector d.o.o., Ljubljana, Slovenia
³Jožef Stefan International Postgraduate School, Ljubljana, Slovenia

Chapter 7. Prediction of General Anxiety Disorder Using Machine Learning Techniques
Kevser Şahinbaş
Management Information Systems, Istanbul Medipol University, Istanbul, Turkey

Index