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Introduction to Data Mining and its Applications by S. Sumathi (English) Paperba
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Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- ISBN-13
- 9783662500804
- Book Title
- Introduction to Data Mining and its Applications
- ISBN
- 9783662500804
- Subject Area
- Mathematics, Computers, Technology & Engineering
- Publication Name
- Introduction to Data Mining and Its Applications
- Publisher
- Springer Berlin / Heidelberg
- Item Length
- 11.7 in
- Subject
- Engineering (General), Probability & Statistics / General, Databases / Data Mining
- Publication Year
- 2016
- Series
- Studies in Computational Intelligence Ser.
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Weight
- 77.4 Oz
- Item Width
- 8.3 in
- Number of Pages
- Xxii, 828 Pages
About this product
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3662500809
ISBN-13
9783662500804
eBay Product ID (ePID)
240469371
Product Key Features
Number of Pages
Xxii, 828 Pages
Publication Name
Introduction to Data Mining and Its Applications
Language
English
Publication Year
2016
Subject
Engineering (General), Probability & Statistics / General, Databases / Data Mining
Type
Textbook
Subject Area
Mathematics, Computers, Technology & Engineering
Series
Studies in Computational Intelligence Ser.
Format
Trade Paperback
Dimensions
Item Weight
77.4 Oz
Item Length
11.7 in
Item Width
8.3 in
Additional Product Features
Dewey Edition
22
Series Volume Number
29
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
006.312
Table Of Content
to Data Mining Principles.- Data Warehousing, Data Mining, and OLAP.- Data Marts and Data Warehouse.- Evolution and Scaling of Data Mining Algorithms.- Emerging Trends and Applications of Data Mining.- Data Mining Trends and Knowledge Discovery.- Data Mining Tasks, Techniques, and Applications.- Data Mining: an Introduction - Case Study.- Data Mining & KDD.- Statistical Themes and Lessons for Data Mining.- Theoretical Frameworks for Data Mining.- Major and Privacy Issues in Data Mining and Knowledge Discovery.- Active Data Mining.- Decomposition in Data Mining - A Case Study.- Data Mining System Products and Research Prototypes.- Data Mining in Customer Value and Customer Relationship Management.- Data Mining in Business.- Data Mining in Sales Marketing and Finance.- Banking and Commercial Applications.- Data Mining for Insurance.- Data Mining in Biomedicine and Science.- Text and Web Mining.- Data Mining in Information Analysis and Delivery.- Data Mining in Telecommunications and Control.- Data Mining in Security.
Synopsis
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization., This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.
LC Classification Number
QA76.9.D343
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