Proceedings of Data Analytics and Management : ICDAM 2023, Volume 1 / edited by Abhishek Swaroop, Zdzislaw Polkowski, Sérgio Duarte Correia, Bal Virdee.

Format:

Book

Contributor:

Swaroop, Abhishek, editor.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 785

Language:

English

Subjects (All):

Computational intelligence.

Telecommunication.

Quantitative research.

Data protection.

Computational Intelligence.

Communications Engineering, Networks.

Data Analysis and Big Data.

Data and Information Security.

Local Subjects:

Computational Intelligence.

Communications Engineering, Networks.

Data Analysis and Big Data.

Data and Information Security.

Physical Description:

1 online resource (696 pages)

Edition:

1st ed. 2024.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2024.

Summary:

This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.

Contents:

Chapter 1: Diagnosis of Parkinson disease using Ensemble methods for Class Imbalance Problem

Chapter 2: A Comparative Analysis of Pneumonia Detection Using Chest X-Rays With DNN

Chapter 3: Machine Learning Based Binary Sentiment Classification of Movie Reviews in Hindi (Devanagari Script)

Chapter 4: Deep Learning-Based Recommendation Systems: Review and Critical Analysis

Chapter 5: Retention in Second Year Computing Students in a London-Based University During The Post-Covid-19 Era Using Learned Optimism as a Lens: A Statistical Analysis in R

Chapter 6: Alzheimer’s Disease Knowledge Graph Based on Ontology and Neo4j Graph Database

Chapter 7: Forecasting Bitcoin Prices in the Context of the COVID19 Pandemic Using Machine Learning Approaches

Chapter 8: Online Food Delivery Customer Churn Prediction: A Quantitative Analysis on the Performance of Machine Learning Classifiers

Chapter 9: Prevention Equipment for COVID-19 Spread Using IoT and Multimedia-Based Solutions

Chapter 10: Renal Disease Classification using Image Processing. etc.

Notes:

Includes bibliographical references and index.

ISBN:

981-9965-44-6