| Description |
1 online resource : text file, PDF |
| Contents |
Cover; Half title; Copy right; Preface; About the Author; Dedication; TABLE OF CONTENTS; Chapter 1. Introduction; 1.1 What is Data Mining; 1.2 Data Mining Technologies; 1.3 Concepts and Techniques in Data Mining; 1.4 Directions and Trends in Data Mining; 1.5 Organization of this Book; 1.6 Additional Discussion of the Contents; 1.7 How Do We Proceed; Part I. Technologies for Data Mining; Introduction to Part I; Chapter 2. Database Systems; 2.1 Overview; 2.2 Data Models; 2.2.1 Overview; 2.2.2 Relational Data Model; 2.2.3 Entity-Relationship Data Model; 2.2.4 Object-Oriented Data Model |
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2.2.5 Object Relational Data Model2.2.6 Logic-Based Data Model; 2.3 Architectural Issues; 2.4 Database Design; 2.5 Database Administration; 2.6 Database Management System Functions; 2.6.1 Overview; 2.6.2 Query Processing; 2.6.3 Transaction Management; 2.6.4 Storage Management; 2.6.5 Metadata Management; 2.6.6 Database Integrity; 2.6.7 Database Security; 2.6.8 Fault Tolerance; 2.7 Database Systems and Mining; 2.7.1 Overview; 2.7.2 Architectural, Modeling, Design and Administration Aspects; 2.7.3 Data Mining and Database Functions; 2.8 Summary; Chapter 3. Data Warehousing; 3.1 Overview |
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3.2 Technologies for Data Warehousing3.3 Developing the Data Warehouse; 3.4 Data Warehousing and Data Mining; 3.5 Summary; Chapter 4. Some Other Technologies for Data Mining 6S 4.1 Overview; 4.2 Statistical Reasoning; 4.3 Machine Learning; 4.4 Visualization; 4.5 Parallel Processing; 4.6 Decision Support; 4.7 Summary; Chapter 5. Architectural Support for Data Mining; 5.1 Overview; 5.2 Integration with Other Technologies; 5.3 Functional Architecture; 5.4 System Architecture; 5.4.1 Overview; 5.4.2 Client-Server Technology; 5.4.3 Relationship to Mining; 5.5 Summary; Conclusion to Part I |
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Part II. Techniques and Tools for Data MiningIntroduction to Part II; Chapter 6. The Process of Data Mining; 6.1 Overview; 6.2 Examples; 6.3 Why Data Mining; 6.4 Steps to Data Mining; 6.5 Challenges; 6.6 User Interface Aspects; 6.7 Summary; Chapter 7. Data Mining Outcomes, Approaches, and Techniques; 7.1 Overview; 7.2 Outcomes of Data Mining; 7.3 Approaches to Data Mining; 7.4 Data Mining Techniques and Algorithms; 7.5 Summary; Chapter 8. Logic Programming as a Data Mining Technique; 8.1 Overview; 8.2 Deductive Logic Programming; 8.3 Inductive Logic Programming |
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8.4 Inductive Logic Programming for Data Mining8.5 Applications of Inductive Logic Programming; 8.6 Summary; Chapter 9. Data Mining Tools; 9.1 Overview; 9.2 Prototypes; 9.2.1 Overview; 9.2.2 New Functional Models; 9.2.3 New Information Services; 9.2.4 Scalability; 9.2.5 Understandability of Results; 9.2.6 Large-Scale Projects; 9.2 Commercial Tools; 9.3.1 Overview; 9.3.2 Product 1; 9.3.3 Product 2; 9.3.4 Product 3; 9.3.5 Product 4; 9.3.6 Product 5; 9.3 Summary; Conclusion to Part II; Part III. Trends in Data Mining; Introduction to Part III |
| Summary |
"Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining:Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data miningPart II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date informationPart III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues. This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence. Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information."--Provided by publisher |
| Subject |
Data mining.
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Electronic data processing -- Data preparation.
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Information technology -- Management.
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Economics -- Statistical methods.
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Commercial statistics.
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Commercial statistics
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Data mining
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Economics -- Statistical methods
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Electronic data processing -- Data preparation
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Information technology -- Management
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| Form |
Electronic book
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| ISBN |
9781482252507 |
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1482252503 |
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