Practical Data Mining Techniques and Applications  book cover
1st Edition

Practical Data Mining Techniques and Applications

  • Available for pre-order on May 29, 2023. Item will ship after June 19, 2023
ISBN 9781032232676
June 19, 2023 Forthcoming by Auerbach Publications
216 Pages 80 B/W Illustrations

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USD $200.00

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Book Description

Data mining techniques and algorithms are extensively used to build real-world applications. A practical approach can be applied to data mining techniques to build applications. An application once deployed enables the developers to work on the users’ goals and mould the algorithms with respect to users’ perspective.

Practical Data Mining Techniques and Applications focuses on various concepts related to data mining and how these techniques can be used to develop and deploy applications. The book provides systematic composition of fundamental concepts of data mining blended with practical applications. The aim of this book is to provide access to practical data mining applications and techniques to help readers gain an understanding of data mining in practice. Readers also learn how relevant techniques and algorithms are applied to solve problems and to provide solutions to real-world applications in different domains. This book can help academicians to extend their knowledge of the field as well as their understanding of applications based on different techniques to gain greater insight. It can also help researchers with real-world applications by diving deeper into the domain. Computing science students, application developers, and business professionals may also benefit from this examination of applied data science techniques.

By highlighting an overall picture of the field, introducing various mining techniques, and focusing on different applications and research directions using these methods, this book can motivate discussions among academics, researchers, professionals, and students to exchange and develop their views regarding the dynamic field that is data mining.

Table of Contents

1. Introduction to Data Mining Techniques
Neepa Shah and Ketan Shah

2. Review of Latent Dirichlet Allocation to Understand Motivations to Share Conspiracy Theory: A Case Study of "Plandemic" during COVID-19
Sushma Kumble, Pratiti Diddi, and Jeff Dean Conlin

3. Near Human-Level Style Transfer
Rahul Pereira, Beryl Coutinho, Dsouza, Cyrus Ferreira, and Vaishali Jadhav

4. Semantics-based Distributed Document Clustering
Neepa Shah, Sunita Mahajan, and Ketan Shah

5. Application of Machine Learning in Disease Prediction
Sannidhi Rao, Shreya Kulkarni, Shikha Mehta, and Neha Katre

6. Federated Machine Learning-based Bank Customer Churn Prediction
Chirag Jagad, Chirag Jain, Dhrumil Thakore, Om Naik, and Vinaya Sawant

7. Challenges and Avenues for Sophisticated Digitized Healthcare System: A Review
Rajesh Shardanand Prasad, Jayashree Rajesh Prasad, and Nihar M Ranjan

8. Unusual Social Media Behavior Detection using Distributed Data Stream Mining
Aakash Sangani, Princy Doshi, and Vinaya Sawant

9. Market Basket Analysis Using Distributed Algorithm
Vinaya Sawant, Ketan Shah, and Neeraj Parolia

10. Identification of Crime Prone Areas using Data Mining Techniques
Jainam Rambhia, Bhoomika Valani, Shivam Vora, Chaitanya Kumbar and Neha Katre

11. Smart Baby Cradle for Infant Soothing and Monitoring
Aditya Adhduk, Ritik Sanghvi, Sahil Lunawat, and Vinaya Sawant

12. Word Level Devanagari Text Recognition
Rutwik Shailesh Shah, Harshil Suresh Bhorawat, Hritik Ganesh Sawant, and Vinaya Sawant

13. Wall Paint Visualizer Using Panoptic Segmentation
Martin Devasia, Sakshi Shetty, Sheldon Moonjelil, Leander Pereira, and Vaishali Jadhav

14. Fashion Intelligence: An Artificial Intelligence-based Clothing Fashion Stylist
Pavan Raval, Raj Shah, Vrutik Adani, Lissa Rodrigues, and Vaishali Jadhav

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Dr. Ketan Shah, Head of Information Technology Department, at SVKM’s NMIMS - Mukesh Patel School of Technology Management and Engineering (MPSTME). He also holds the additional responsibility of Associate Dean (Accreditations) at MPSTME. In this role, he has successfully spearheaded the ABET accreditation of five programs at MPSTME. All the five programs have got ABET accreditation for six years up to 2026. He has his Bachelors and Master Degree in Electronics Engineering from Mumbai University and PhD in Engineering from NMIMS. He has 23 years of teaching experience and has taught undergraduate and postgraduate students. He has also guided 5 doctoral students who have successfully completed their PhD. His research area is Data Mining. He has 15 Journal papers and 25 conference papers to his credit.

Dr. Neepa Shah, Ex-Head of Information Technology Department, at Dwarkadas J. Sanghvi College of Engineering, Mumbai University. She is devoted to education, and always interested in applying new things. She graduated in the year 2001 from Pune University, completed her M. Tech. in 2008, and PhD in the year 2017 and has teaching experience of 20+ years (since 2001). Along with teaching different subjects and guiding students for placement and higher studies, she has played different roles simultaneously. To mention a few, vice-chair of software team, admission committee, program chair for NBA committee, technical chair for the international conference, ICACTA and DJ ASCII-State level project competition, and many more. She has also implemented a few inhouse software for DJSCE. She is a registered and recognized coach for the International Collegiate Programming Competition (ACM-ICPC) since 2006. She has also participated in 50+ workshops and STTPs. She has published 30+ papers in various international and national journals / conferences. She has received Research Grant in a. y. 2015-16 from University of Mumbai of Amount Rs. 25,000/-. She is also an award winner of "BEST FACULTY" in 2008. Her areas of specialization include Data Mining, Semantics, Natural Language Processing, Parallel Computing, and Distributed Systems. She has delivered special talks on advanced algorithms, semantics, and distributed document clustering in a few institutes.

Dr. Vinaya Sawant, Head of Information Technology Department of Dwarkadas J. Sanghvi College of Engineering, Mumbai University, possesses an experience of 19 years in teaching subjects such as Database Management Systems, Advanced Databases, Data Warehousing and Mining, Data Analytics, Distributed Systems, Image Processing. Apart from academic activities, she is also involved in administrative committees at the college level as well as actively interacted outside college in many ways. She was invited as reviewers in many International Conferences. Also, she has conducted many guest lectures in other Universities. She has successfully completed her Masters (M. Tech) in Computer Engineering in 2010 from NMIMS University and secured first place at the University level. She then completed her PhD degree from the same University, in the year 2020. Her research is directed towards proposing and implementing the distributed data mining algorithms that aims to reduce the execution time and communication overhead in a distributed environment, effectively and efficiently. Her work is highlighted in 25+ recognized international publications (Scopus indexed) such as IEEE, Elsevier, Springer, etc. Her active participation in conferences shows her ability to work in the current research areas and diving deep into it. She is more inclined towards the current trends of applied data mining and interested in contributing to that direction.

Dr. Neeraj Parolia is an Associate Professor in the Business Analytics and Technology Management Department at Towson University. He received his PhD from the University of Central Florida. His research interests include IT Project and Program Management. His research has been published in Information and Management, International Journal of Project Management, Information and Software Technology, Electronic Journal of Information Systems Evaluation, International Journal of Information Technology Project Management and International Journal of Project Organization and Management. Neeraj is an active participant in the AIS SIG of Information Technology Project Management and has served on the board of the American Society for the Advancement of Project Management as Director of Education.