SlideShare uma empresa Scribd logo

Chapter 1. Introduction

•Transferir como PPT, PDF•
•
B
butest
1 de 52
Data Mining: Concepts and Techniques — Chapter 1 — — Introduction — ,[object Object],[object Object],[object Object],[object Object],[object Object]
 
Data and Information Systems (DAIS:) Course Structures at CS/UIUC ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CS412 Coverage (Chapters 1-7 of This Book) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
CS512 Coverage (Chapters 8-11 of This Book) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Chapter 1. Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Data Mining? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Evolution of Sciences ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Evolution of Database Technology ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What Is Data Mining? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Knowledge Discovery (KDD) Process ,[object Object],Data Cleaning Data Integration Databases Data Warehouse Knowledge Task-relevant Data Selection Data Mining Pattern Evaluation
Data Mining and Business Intelligence Increasing potential to support business decisions End User Business Analyst Data Analyst DBA Decision Making Data Presentation Visualization Techniques Data Mining Information Discovery Data Exploration Statistical Summary, Querying, and Reporting Data Preprocessing/Integration, Data Warehouses Data Sources Paper, Files, Web documents, Scientific experiments, Database Systems
Data Mining: Confluence of Multiple Disciplines Data Mining Database Technology Statistics Machine Learning Pattern Recognition Algorithm Other Disciplines Visualization
Why Not Traditional Data Analysis? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multi-Dimensional View of Data Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining: Classification Schemes ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining: On What Kinds of Data? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining Functionalities ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mining Functionalities (2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Top-10 Most Popular DM Algorithms: 18 Identified Candidates (I) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The 18 Identified Candidates (II) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The 18 Identified Candidates (III) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Top-10 Algorithm Finally Selected at ICDM’06 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Major Issues in Data Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A Brief History of Data Mining Society ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Conferences and Journals on Data Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Where to Find References? DBLP, CiteSeer, Google ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Recommended Reference Books ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Supplementary Lecture Slides ,[object Object],[object Object],[object Object]
Why Data Mining?—Potential Applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ex. 1: Market Analysis and Management ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ex. 2: Corporate Analysis & Risk Management ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ex. 3: Fraud Detection & Mining Unusual Patterns ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
KDD Process: Several Key Steps ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Are All the “Discovered” Patterns Interesting? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Find All and Only Interesting Patterns? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Other Pattern Mining Issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A Few Announcements (Sept. 1) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Data Mining Query Language? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Primitives that Define a Data Mining Task ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Primitive 3: Background Knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Primitive 4: Pattern Interestingness Measure ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Primitive 5: Presentation of Discovered Patterns ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
DMQL—A Data Mining Query Language ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
An Example Query in DMQL
Other Data Mining Languages & Standardization Efforts ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Integration of Data Mining and Data Warehousing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Coupling Data Mining with DB/DW Systems ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Architecture: Typical Data Mining System data cleaning, integration, and selection Database or Data Warehouse Server Data Mining Engine Pattern Evaluation Graphical User Interface Knowledge-Base Database Data Warehouse World-Wide Web Other Info Repositories

Recomendados

introduction to data mining tutorial
introduction to data mining tutorial introduction to data mining tutorial
introduction to data mining tutorial
Salah Amean
 
Data Quality
Data QualityData Quality
Data Quality
Michael Collins
 
Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5
Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5 Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5
Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5
Salah Amean
 
Strategy For Data Quality
Strategy For Data QualityStrategy For Data Quality
Strategy For Data Quality
Database Answers Ltd.
 
Data Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessing
Data Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessingData Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessing
Data Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessing
Salah Amean
 
Data Preprocessing
Data PreprocessingData Preprocessing
Data Preprocessing
Object-Frontier Software Pvt. Ltd
 
Data Mining: Concepts and Techniques — Chapter 2 —
Data Mining: Concepts and Techniques — Chapter 2 —Data Mining: Concepts and Techniques — Chapter 2 —
Data Mining: Concepts and Techniques — Chapter 2 —
Salah Amean
 
Data analytics introduction
Data analytics introductionData analytics introduction
Data analytics introduction
amiyadash
 

Recomendados

introduction to data mining tutorial
introduction to data mining tutorial introduction to data mining tutorial
introduction to data mining tutorial
Salah Amean
 
Data Quality
Data QualityData Quality
Data Quality
Michael Collins
 
Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5
Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5 Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5
Data Mining: Concepts and Techniques (3rd ed.) — Chapter 5
Salah Amean
 
Strategy For Data Quality
Strategy For Data QualityStrategy For Data Quality
Strategy For Data Quality
Database Answers Ltd.
 
Data Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessing
Data Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessingData Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessing
Data Mining: Concepts and Techniques (3rd ed.) - Chapter 3 preprocessing
Salah Amean
 
Data Preprocessing
Data PreprocessingData Preprocessing
Data Preprocessing
Object-Frontier Software Pvt. Ltd
 
Data Mining: Concepts and Techniques — Chapter 2 —
Data Mining: Concepts and Techniques — Chapter 2 —Data Mining: Concepts and Techniques — Chapter 2 —
Data Mining: Concepts and Techniques — Chapter 2 —
Salah Amean
 
Data analytics introduction
Data analytics introductionData analytics introduction
Data analytics introduction
amiyadash
 
data mining
data miningdata mining
data mining
uoitc
 
Data warehouse presentaion
Data warehouse presentaionData warehouse presentaion
Data warehouse presentaion
sridhark1981
 
Data preprocessing
Data preprocessingData preprocessing
Data preprocessing
Jason Rodrigues
 
DATA Warehousing & Data Mining
DATA Warehousing & Data MiningDATA Warehousing & Data Mining
DATA Warehousing & Data Mining
cpjcollege
 
A Data Curation Framework: Data Curation and Research Support Services
A Data Curation Framework: Data Curation and Research Support ServicesA Data Curation Framework: Data Curation and Research Support Services
A Data Curation Framework: Data Curation and Research Support Services
SusanMRob
 
Data warehouse and Decision support system
Data warehouse and Decision support system Data warehouse and Decision support system
Data warehouse and Decision support system
Enaam Alotaibi
 
Demystifying Data Warehousing as a Service (GLOC 2019)
Demystifying Data Warehousing as a Service (GLOC 2019)Demystifying Data Warehousing as a Service (GLOC 2019)
Demystifying Data Warehousing as a Service (GLOC 2019)
Kent Graziano
 
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Amazon Web Services
 
Chapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
Chapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & KamberChapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
Chapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
error007
 
Data Quality & Data Governance
Data Quality & Data GovernanceData Quality & Data Governance
Data Quality & Data Governance
Tuba Yaman Him
 
Introduction
IntroductionIntroduction
Introduction
neelamoberoi1030
 
Big data architectures and the data lake
Big data architectures and the data lakeBig data architectures and the data lake
Big data architectures and the data lake
James Serra
 
Data Mining:Concepts and Techniques, Chapter 8. Classification: Basic Concepts
Data Mining:Concepts and Techniques, Chapter 8. Classification: Basic ConceptsData Mining:Concepts and Techniques, Chapter 8. Classification: Basic Concepts
Data Mining:Concepts and Techniques, Chapter 8. Classification: Basic Concepts
Salah Amean
 
DBMS an Example
DBMS an ExampleDBMS an Example
DBMS an Example
Dr. C.V. Suresh Babu
 
Data mining PPT
Data mining PPTData mining PPT
Data mining PPT
Kapil Rode
 
Data preparation
Data preparationData preparation
Data preparation
Tony Nguyen
 
Data quality and data profiling
Data quality and data profilingData quality and data profiling
Data quality and data profiling
Shailja Khurana
 
Data management
Data managementData management
Data management
RahulJoshi975765
 
Data Warehouse or Data Lake, Which Do I Choose?
Data Warehouse or Data Lake, Which Do I Choose?Data Warehouse or Data Lake, Which Do I Choose?
Data Warehouse or Data Lake, Which Do I Choose?
DATAVERSITY
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence data
DataminingTools Inc
 
Introduction to data warehouse
Introduction to data warehouseIntroduction to data warehouse
Introduction to data warehouse
Cognizant Technology Solutions
 
Unit 1 (Chapter-1) on data mining concepts.ppt
Unit 1 (Chapter-1) on data mining concepts.pptUnit 1 (Chapter-1) on data mining concepts.ppt
Unit 1 (Chapter-1) on data mining concepts.ppt
PadmajaLaksh
 

Mais conteúdo relacionado

Mais procurados

DATA Warehousing & Data Mining
DATA Warehousing & Data MiningDATA Warehousing & Data Mining
DATA Warehousing & Data Mining
cpjcollege
 
Data warehouse and Decision support system
Data warehouse and Decision support system Data warehouse and Decision support system
Data warehouse and Decision support system
Enaam Alotaibi
 
Big data architectures and the data lake
Big data architectures and the data lakeBig data architectures and the data lake
Big data architectures and the data lake
James Serra
 
Data mining PPT
Data mining PPTData mining PPT
Data mining PPT
Kapil Rode
 
Data Warehouse or Data Lake, Which Do I Choose?
Data Warehouse or Data Lake, Which Do I Choose?Data Warehouse or Data Lake, Which Do I Choose?
Data Warehouse or Data Lake, Which Do I Choose?
DATAVERSITY
 

Mais procurados (20)

data mining
data miningdata mining
data mining
 
Data warehouse presentaion
Data warehouse presentaionData warehouse presentaion
Data warehouse presentaion
 
Data preprocessing
Data preprocessingData preprocessing
Data preprocessing
 
DATA Warehousing & Data Mining
DATA Warehousing & Data MiningDATA Warehousing & Data Mining
DATA Warehousing & Data Mining
 
A Data Curation Framework: Data Curation and Research Support Services
A Data Curation Framework: Data Curation and Research Support ServicesA Data Curation Framework: Data Curation and Research Support Services
A Data Curation Framework: Data Curation and Research Support Services
 
Data warehouse and Decision support system
Data warehouse and Decision support system Data warehouse and Decision support system
Data warehouse and Decision support system
 
Demystifying Data Warehousing as a Service (GLOC 2019)
Demystifying Data Warehousing as a Service (GLOC 2019)Demystifying Data Warehousing as a Service (GLOC 2019)
Demystifying Data Warehousing as a Service (GLOC 2019)
 
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
Easy Analytics on AWS with Amazon Redshift, Amazon QuickSight, and Amazon Mac...
 
Chapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
Chapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & KamberChapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
Chapter - 6 Data Mining Concepts and Techniques 2nd Ed slides Han & Kamber
 
Data Quality & Data Governance
Data Quality & Data GovernanceData Quality & Data Governance
Data Quality & Data Governance
 
Introduction
IntroductionIntroduction
Introduction
 
Big data architectures and the data lake
Big data architectures and the data lakeBig data architectures and the data lake
Big data architectures and the data lake
 
Data Mining:Concepts and Techniques, Chapter 8. Classification: Basic Concepts
Data Mining:Concepts and Techniques, Chapter 8. Classification: Basic ConceptsData Mining:Concepts and Techniques, Chapter 8. Classification: Basic Concepts
Data Mining:Concepts and Techniques, Chapter 8. Classification: Basic Concepts
 
DBMS an Example
DBMS an ExampleDBMS an Example
DBMS an Example
 
Data mining PPT
Data mining PPTData mining PPT
Data mining PPT
 
Data preparation
Data preparationData preparation
Data preparation
 
Data quality and data profiling
Data quality and data profilingData quality and data profiling
Data quality and data profiling
 
Data management
Data managementData management
Data management
 
Data Warehouse or Data Lake, Which Do I Choose?
Data Warehouse or Data Lake, Which Do I Choose?Data Warehouse or Data Lake, Which Do I Choose?
Data Warehouse or Data Lake, Which Do I Choose?
 
Data Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence dataData Mining: Mining stream time series and sequence data
Data Mining: Mining stream time series and sequence data
 

Semelhante a Chapter 1. Introduction

Unit 1 (Chapter-1) on data mining concepts.ppt
Unit 1 (Chapter-1) on data mining concepts.pptUnit 1 (Chapter-1) on data mining concepts.ppt
Unit 1 (Chapter-1) on data mining concepts.ppt
PadmajaLaksh
 
Dwdmunit1 a
Dwdmunit1 aDwdmunit1 a
Dwdmunit1 a
bhagathk
 

Semelhante a Chapter 1. Introduction (20)

Introduction to data warehouse
Introduction to data warehouseIntroduction to data warehouse
Introduction to data warehouse
 
Unit 1 (Chapter-1) on data mining concepts.ppt
Unit 1 (Chapter-1) on data mining concepts.pptUnit 1 (Chapter-1) on data mining concepts.ppt
Unit 1 (Chapter-1) on data mining concepts.ppt
 
Chapter 1. Introduction.ppt
Chapter 1. Introduction.pptChapter 1. Introduction.ppt
Chapter 1. Introduction.ppt
 
Cs501 dm intro
Cs501 dm introCs501 dm intro
Cs501 dm intro
 
01 Data Mining: Concepts and Techniques, 2nd ed.
01 Data Mining: Concepts and Techniques, 2nd ed.01 Data Mining: Concepts and Techniques, 2nd ed.
01 Data Mining: Concepts and Techniques, 2nd ed.
 
Dwdm
DwdmDwdm
Dwdm
 
Dm lecture1
Dm lecture1Dm lecture1
Dm lecture1
 
Introduction to Data Mining
Introduction to Data MiningIntroduction to Data Mining
Introduction to Data Mining
 
Data Mining Intro
Data Mining IntroData Mining Intro
Data Mining Intro
 
data mining
data miningdata mining
data mining
 
01Intro.ppt
01Intro.ppt01Intro.ppt
01Intro.ppt
 
01Introduction to data mining chapter 1.ppt
01Introduction to data mining chapter 1.ppt01Introduction to data mining chapter 1.ppt
01Introduction to data mining chapter 1.ppt
 
01Intro.ppt
01Intro.ppt01Intro.ppt
01Intro.ppt
 
Data Mining introduction and basic concepts
Data Mining introduction and basic conceptsData Mining introduction and basic concepts
Data Mining introduction and basic concepts
 
Upstate CSCI 525 Data Mining Chapter 1
Upstate CSCI 525 Data Mining Chapter 1Upstate CSCI 525 Data Mining Chapter 1
Upstate CSCI 525 Data Mining Chapter 1
 
unit 1 DATA MINING.ppt
unit 1 DATA MINING.pptunit 1 DATA MINING.ppt
unit 1 DATA MINING.ppt
 
Dwdmunit1 a
Dwdmunit1 aDwdmunit1 a
Dwdmunit1 a
 
Lect 1 introduction
Lect 1 introductionLect 1 introduction
Lect 1 introduction
 
Lect 1 introduction
Lect 1 introductionLect 1 introduction
Lect 1 introduction
 
Introduction to Data Mining and technologies .ppt
Introduction to Data Mining and technologies .pptIntroduction to Data Mining and technologies .ppt
Introduction to Data Mining and technologies .ppt
 

Mais de butest

EL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBEEL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBE
butest
 
1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同
butest
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIAL
butest
 
Timeline: The Life of Michael Jackson
Timeline: The Life of Michael JacksonTimeline: The Life of Michael Jackson
Timeline: The Life of Michael Jackson
butest
 
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
butest
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIAL
butest
 
Com 380, Summer II
Com 380, Summer IICom 380, Summer II
Com 380, Summer II
butest
 
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet JazzThe MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
butest
 
MICHAEL JACKSON.doc
MICHAEL JACKSON.docMICHAEL JACKSON.doc
MICHAEL JACKSON.doc
butest
 
Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1
butest
 
Facebook
Facebook Facebook
Facebook
butest
 
Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...
butest
 
Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...
butest
 
NEWS ANNOUNCEMENT
NEWS ANNOUNCEMENTNEWS ANNOUNCEMENT
NEWS ANNOUNCEMENT
butest
 
C-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.docC-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.doc
butest
 
MAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.docMAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.doc
butest
 
Mac OS X Guide.doc
Mac OS X Guide.docMac OS X Guide.doc
Mac OS X Guide.doc
butest
 
WEB DESIGN!
WEB DESIGN!WEB DESIGN!
WEB DESIGN!
butest
 

Mais de butest (20)

EL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBEEL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBE
 
1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIAL
 
Timeline: The Life of Michael Jackson
Timeline: The Life of Michael JacksonTimeline: The Life of Michael Jackson
Timeline: The Life of Michael Jackson
 
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIAL
 
Com 380, Summer II
Com 380, Summer IICom 380, Summer II
Com 380, Summer II
 
PPT
PPTPPT
PPT
 
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet JazzThe MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
 
MICHAEL JACKSON.doc
MICHAEL JACKSON.docMICHAEL JACKSON.doc
MICHAEL JACKSON.doc
 
Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1
 
Facebook
Facebook Facebook
Facebook
 
Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...
 
Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...
 
NEWS ANNOUNCEMENT
NEWS ANNOUNCEMENTNEWS ANNOUNCEMENT
NEWS ANNOUNCEMENT
 
C-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.docC-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.doc
 
MAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.docMAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.doc
 
Mac OS X Guide.doc
Mac OS X Guide.docMac OS X Guide.doc
Mac OS X Guide.doc
 
hier
hierhier
hier
 
WEB DESIGN!
WEB DESIGN!WEB DESIGN!
WEB DESIGN!
 

Chapter 1. Introduction

  • 1.
  • 2.  
  • 3.
  • 4.
  • 5.
  • 6.  
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. Data Mining and Business Intelligence Increasing potential to support business decisions End User Business Analyst Data Analyst DBA Decision Making Data Presentation Visualization Techniques Data Mining Information Discovery Data Exploration Statistical Summary, Querying, and Reporting Data Preprocessing/Integration, Data Warehouses Data Sources Paper, Files, Web documents, Scientific experiments, Database Systems
  • 14. Data Mining: Confluence of Multiple Disciplines Data Mining Database Technology Statistics Machine Learning Pattern Recognition Algorithm Other Disciplines Visualization
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.  
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44.
  • 45.
  • 46.
  • 47.
  • 48. An Example Query in DMQL
  • 49.
  • 50.
  • 51.
  • 52. Architecture: Typical Data Mining System data cleaning, integration, and selection Database or Data Warehouse Server Data Mining Engine Pattern Evaluation Graphical User Interface Knowledge-Base Database Data Warehouse World-Wide Web Other Info Repositories