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1 1 Bab I Intro to Data Mining Jiawei Han, Micheline Kamber, and Jian Pei University of Illinois at Urbana-Champaign & Simon Fraser University ©2013 Han, Kamber & Pei. All rights reserved. 2 Chapter 1. Introduction  Why Data Mining?  What Is Data Mining?  A Multi-Dimensional View of Data Mining  What Kinds of Data Can Be Mined?  What Kinds of Patterns Can Be Mined?  What Kinds of Technologies Are Used?  What Kinds of Applications Are Targeted?  Major Issues in
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  1 1 Bab I  Intro to Data Mining Jiawei Han, Micheline Kamber, and Jian Pei University of Illinois at Urbana-Champaign & Simon Fraser University ©2013 Han, Kamber & Pei. All rights reserved.  2 Chapter 1. Introduction  Why Data Mining?  What Is Data Mining?  A Multi-Dimensional View of Data Mining  What Kinds of Data Can Be Mined?  What Kinds of Patterns Can Be Mined?  What Kinds of Technologies Are Used?  What Kinds of Applications Are Targeted?  Major Issues in Data Mining  A Brief History of Data Mining and Data Mining Society  Summary  3 Why Data Mining?  The Explosive Growth of Data: from terabytes to petabytes  Data collection and data availability  Automated data collection tools, database systems, Web, computerized society  Major sources of abundant data  Business: Web, e- commerce, transactions, stocks, …  Science: Remote sensing, bioinformatics, scientific simulation, …  Society and everyone: news, digital cameras, YouTube  We are drowning in data, but starving for knowledge!  “Necessity is the mother of invention”— Data mining — Automated analysis of massive data sets  4 Chapter 1. Introduction  Why Data Mining?  What Is Data Mining?  A Multi-Dimensional View of Data Mining  What Kinds of Data Can Be Mined?  What Kinds of Patterns Can Be Mined?  What Kinds of Technologies Are Used?  What Kinds of Applications Are Targeted?  Major Issues in Data Mining  A Brief History of Data Mining and Data Mining Society  Summary
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