Technologies for big data / Kapil Bakshi -- Applying the K-means algorithm in big raw data sets with Hadoop and MapReduce / Ilias K. Savvas, Georgia N. Sofianidou, M-Tahar Kechadi -- Synchronizing execution of big data in distributed and parallelized environments / Gueyoung Jung, Tridib...

"This book provides an analysis of large data in the field of classification and clustering by presenting algorithms and comparative analysis in the form of their effectiveness and efficiency. It covers topics such as handling large data with conventional data mining, machine learning algorithms...

Preface -- 1 Ranking -- 2 Online Learning -- 3 Recommendation Systems -- 4 Classification -- 5 Clustering -- 6 Linear Regression -- 7 Sparse Recovery -- 8 Neural Networks -- 9 Decision Trees -- 10 Solutions.

"Foreword Big data and analytics promise to change virtually every industry and business function over the next decade. Any organization that gets started early with big data can gain a significant competitive edge. Just as early analytical competitors in the "small data" era (including Capital...

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- List of Tutorials -- List of Figures/Illustrations -- Foreword -- Preface -- Acknowledgements -- Author -- Chapter 1: Introduction to Big Data -- OVERVIEW -- RAPID GROWTH OF BIG DATA -- BIG DATA DEFINITION -- BIG...

"This book explores how big data technologies can address the operational challenges in the railway industry. It assists academics working in the big data domain to gain an understanding of the problems faced by the rail industry, enabling them to start developing their existing tools and...

"[This book] is a key source on the latest advancements in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. Featuring extensive coverage across a range of relevant perspectives and topics, such as visual...