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SOCIAL IMPACTS & TRENDS OF DATA
MINING
SUSHIL DHAKAL
1
Data Privacy
Web MiningInformation Security
Data Mining
language
Visual Data Mining
Clickstreams
Biometric
Encryption
Blind
Signatures
Constraint-Based Mining
2
OVERVIEW
INTRODUCTION
• The social impacts of data mining so fast due to
computerization of society.
• The diversity of data, data mining tasks, and
data mining approaches poses many
challenging research issues in data mining.
3
IS DATA MINING A HYPE OR A
PERSISTENT, STEADILY GROWING
BUSINESS?
• Data mining is a technology.
1. Innovators
2. Early Adopters:
3. Chasm:
4. Early Majority:
5. Late Majority:
6. Laggards:
4
IS DATA MINING A HYPE OR A
PERSISTENT, STEADILY GROWING
BUSINESS?
• Customer Relationship Management (CRM)
• Clickstreams
• Customer profiling
• Cross Market Analysis
• Resource Planning
• Competition
• Target marketing
5
IS DATA MINING MERELY MANAGER’S
BUSINESS OR EVERYONE’S BUSINESS?
• Data on the Web and disks — benefit work and
daily life.
• Mine medical history —lifestyles and health.
• Mine the records of the companies —evaluate
their customer service.
• Mine data on stocks and company —financial
investments.
• Invisible data mining:
6
IS DATA MINING A THREAT TO
PRIVACY AND DATA SECURITY?
• Profiling information can be collected every
time!
• Blind Signatures and Biometric Encryption
• Fair Information Practices:
1. Purpose specification and use limitation:
2. Openness:
7
TRENDS OF DATA MINING
1. Application Exploration:
2. Scalable Data Mining Methods:
3. Integration of Data Mining with Database Systems, Data
Warehouse Systems, and Web Database Systems:
4. Standardization of Data Mining language:
5. Visual Data Mining:
6. New methods for mining complex types of data:
7. Web Mining:
8. Privacy protection and information security data mining:
8
Any Queries?
9
Thank You!
10

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Social Impacts & Trends of Data Mining

  • 1. SOCIAL IMPACTS & TRENDS OF DATA MINING SUSHIL DHAKAL 1
  • 2. Data Privacy Web MiningInformation Security Data Mining language Visual Data Mining Clickstreams Biometric Encryption Blind Signatures Constraint-Based Mining 2 OVERVIEW
  • 3. INTRODUCTION • The social impacts of data mining so fast due to computerization of society. • The diversity of data, data mining tasks, and data mining approaches poses many challenging research issues in data mining. 3
  • 4. IS DATA MINING A HYPE OR A PERSISTENT, STEADILY GROWING BUSINESS? • Data mining is a technology. 1. Innovators 2. Early Adopters: 3. Chasm: 4. Early Majority: 5. Late Majority: 6. Laggards: 4
  • 5. IS DATA MINING A HYPE OR A PERSISTENT, STEADILY GROWING BUSINESS? • Customer Relationship Management (CRM) • Clickstreams • Customer profiling • Cross Market Analysis • Resource Planning • Competition • Target marketing 5
  • 6. IS DATA MINING MERELY MANAGER’S BUSINESS OR EVERYONE’S BUSINESS? • Data on the Web and disks — benefit work and daily life. • Mine medical history —lifestyles and health. • Mine the records of the companies —evaluate their customer service. • Mine data on stocks and company —financial investments. • Invisible data mining: 6
  • 7. IS DATA MINING A THREAT TO PRIVACY AND DATA SECURITY? • Profiling information can be collected every time! • Blind Signatures and Biometric Encryption • Fair Information Practices: 1. Purpose specification and use limitation: 2. Openness: 7
  • 8. TRENDS OF DATA MINING 1. Application Exploration: 2. Scalable Data Mining Methods: 3. Integration of Data Mining with Database Systems, Data Warehouse Systems, and Web Database Systems: 4. Standardization of Data Mining language: 5. Visual Data Mining: 6. New methods for mining complex types of data: 7. Web Mining: 8. Privacy protection and information security data mining: 8