eBooks-it.org Logo
eBooks-IT.org Inner Image

Data Mining

The Textbook

Data Mining Image

Book Details:

Series: Springer
Author:Charu C. Aggarwal
Published:Apr 27 2015
Posted:Aug 04 2016
Book format:PDF
Book size:5.48 MB

Book Description:

This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples.Praise for Data Mining: The Textbook - As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. Its a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology"This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at Chicago

Download Link:

Related Books:

Mining the Social Web

Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub and More
Mining the Social Web Image
2nd Edition
How can you tap into the wealth of social web data to discover who's making connections with whom, what they're talking about, and where they're located? With this expanded and thoroughly revised edition, you'll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs.Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sitesApply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language dataBootstrap interest graphs from GitHub by discoveri...

Data Science for Business

What you need to know about data mining and data-analytic thinking
Data Science for Business Image
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You'll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company's data science proje...

Making Sense of Data I

A Practical Guide to Exploratory Data Analysis and Data Mining
Making Sense of Data I Image
2nd Edition
Praise for the First Edition ...a well-written book on data analysis and data mining that provides an excellent foundation... -CHOICE This is a must-read book for learning practical statistics and data analysis... -Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors'; practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide r...

Data Mining with Rattle and R

The Art of Excavating Data for Knowledge Discovery
Data Mining with Rattle and R Image
Data Mining and Anlaytics are the foundation technologies for the new knowledge based world where we build models from data and databases to understand and explore our world. Data mining can improve our business, improve our government, and improve our life and with the right tools, any one can begin to explore this new technology, on the path to becoming a data mining professional. This book aims to get you into data mining quickly. Load some data (e.g., from a database) into the Rattle toolkit and within minutes you will have the data visualised and some models built. This is the first step in a journey to data mining and analytics. The book encourages the concept of programming by example and programming with data - more than just pushing data thr...

2007 - 2018 © eBooks-IT.org