Charu C. Aggarwal - Data Mining: The Textbook [2015, PDF, ENG]

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WarriorOfTheDark · 02-Июн-15 21:18 (10 лет 1 месяц назад)

Data Mining: The Textbook
Год: 2015
Автор: Charu C. Aggarwal
Жанр: Программирование
Издательство: Springer
ISBN: 978-3319141411
Язык: Английский
Формат: PDF
Качество: Изначально компьютерное (eBook)
Интерактивное оглавление: Да
Количество страниц: 734
Описание: 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.
Примеры страниц
Оглавление
Table of contents
An Introduction to Data Mining
Pages 1-26
Data Preparation
Pages 27-62
Similarity and Distances
Pages 63-91
Association Pattern Mining
Pages 93-133
Association Pattern Mining: Advanced Concepts
Pages 135-152
Cluster Analysis
Pages 153-204
Cluster Analysis: Advanced Concepts
Pages 205-236
Outlier Analysis
Pages 237-263
Outlier Analysis: Advanced Concepts
Pages 265-283
Data Classification
Pages 285-344
Data Classification: Advanced Concepts
Pages 345-387
Mining Data Streams
Pages 389-427
Mining Text Data
Pages 429-455
Mining Time Series Data
Pages 457-491
Mining Discrete Sequences
Pages 493-529
Mining Spatial Data
Pages 531-555
Mining Graph Data
Pages 557-587
Mining Web Data
Pages 589-617
Social Network Analysis
Pages 619-661
Privacy-Preserving Data Mining
Pages 663-693
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