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

Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics
1. Auflage 2017
ISBN: 978-1-4987-6394-3
Verlag: CRC Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 224 Seiten

Reihe: Chapman & Hall/CRC Computer Science & Data Analysis

This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It covers a diverse range of topics from the field, including data visualization, information search, data sparsity, high dimensional spaces, social media, text analysis, etc. It is written in an accessible style, with lots of detailed case studies to illustrate the methods. R code is integrated throughout to give guidance on implementation of the methods, and code and data is provided on a supplementary website. It is hoped that researchers new to the field can use the book to gain a grounding in the topic and find new research directions.

Autoren/Hrsg.

Murtagh, Fionn

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

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