Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics

" Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching." - Mark Girolami, Warwick University Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge. Preface Part I. Narratives from Film and Literature, from Social Media and Contemporary Life The Correspondence Analysis Platform for Mapping Semantics Analysis and Synthesis of Narrative: Semantics of Interactivity Part II. Foundations of Analytics through the Geometry and Topology of Complex Systems Symmetry in Data Mining and Analysis through Hierarchy Geometry and Topology of Data Analysis: in p-Adic Terms Part III. New Challenges and New Solutions for Information Search and Discovery Fast, Linear Time, m-Adic Hierarchical Clustering Big Data Scaling through Metric Mapping Part IV. New Frontiers: New Vistas on Information, Cognition and on the Human Mind On Ultrametric Algorithmic Information Geometry and Topology of Matte Blanco's Bi-Logic in Psychoanalytics Ultrametric Model of Mind: Application to Text Content Analysis Concluding Discussion on Software Environments "Fionn Murtagh new book is an advanced text in data science which is highly recommended for those seeking for new directions in the field. From the use of ultrametric spaces for modeling the human mind to the study of narratives through hierarchical structures, this book is thought provoking and intellectually challenging." — Prof. Y. Neuman , Ben-Gurion University of the Negev, author of Introduction to Computational Cultural Psychology "Overall, I think this book bring new insights in data science. Many books can be found for the basics of data science. In this book, on the contrary, the approach which is discussed goes a step further. This book is quite technical in some par