Transcript Interactive Data Mining and Business Applications Rayid Ghani Collaboration with Chad Cumby, Divna Djordjevic, Andy Fano, Marko Krema, Mohit Kumar, Abhimanyu Lad, Yiming.

Interactive Data Mining and Business Applications
Rayid Ghani
Collaboration with Chad Cumby, Divna Djordjevic, Andy Fano,
Marko Krema, Mohit Kumar, Abhimanyu Lad, Yiming Yang
Tradeoffs
Cost
(Time of human expert)
Exploration-Exploitation Tradeoffs
Exploration
Exploitation
(Relevancy to the expert)
(Future classifier
performance)
Standard Ranking / Relevance Feedback
Active Learning
Rayid Ghani
Accenture Technology Labs
Case Studies
Product Attribute
Discovery &
Extraction
Health Insurance: Error
Detection in Claims
Social Media: Sentiment
Analysis
Rayid Ghani
Knowledge Management:
Form Filling
Accenture Technology Labs
Tradeoffs in Interactive Data Mining
Cost
(Time of human expert)
Product Attribute
Discovery &
Extraction
Health Insurance: Error
Detection in Claims
Exploration
Exploitation
(Future classifier
performance)
(Relevancy to the expert)
Knowledge Management:
Form Filling
Rayid Ghani
Accenture Technology Labs
System Demo
4
Rayid Ghani
Accenture Technology Labs
More Like This strategy
Select Top m%
claims
Cluster
Rank
Labeled Data
Ranked List scored by
classifier
Online
Strategy
Rayid Ghani
Accenture Technology Labs
Live System Results
~$10 Million savings/year for a
typical insurance company
Precision
0.6
• 27% reduction in audit
time
250
0.5
Precision
0.4
Time Taken per
audit
200
150
0.3
100
0.2
50
0.1
0
0
Baseline - batch More-Like-This
classifier
Rayid Ghani
Accenture Technology Labs
Time(seconds)
• 90% relative improvement
in accuracy over standard
system
Summary
• Interactive Data Mining settings are prevalent in
many business applications
• Challenge: efficiently calculate the incremental
cost and benefit of any information that passes
between expert and data mining system
• Allows users to control and manage tradeoffs
making adoption easier and faster
Rayid Ghani
Accenture Technology Labs