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LEXISNEXIS,
NCSTATE
OPPORTUNITIES
TIM MENZIES
COMPUTER SCIENCE,
JUNE 2015
SEBIG LAB : SE FOR BIG DATA
• Three year partnership
• New lab to explore SE methods for big data apps.
• Grow skill set of engineers:
• Assess different approaches to Big Data
• Validation of results
2
LAB PROCESSES VS
INDUSTRIAL PROCESSES
• Lab processes
• Make 10ml of
oxygen?
• Easy!
• Make 100,000 liters
per day?
• That’s another matter
3
INDUSTRIAL PROCESSES FOR
DATA MINING
4
INDUSTRIAL PROCESSES
FOR DATA MINING
5
1
23
4
5
EXPLORING NEW ALGORITHMS
• New ideas
• SVM
• Deep learning
• Ensembles
• etc
• Visualizations
• Parameter tuning
• Synonym discovery
• Incremental association
rule learning
6
1
VALIDATION STUDIES
• Independent checks of industrial results
• Optimizing validation:
• ? Mechanical Turk
• Better support tools for coding new
functionality
• Better test suites for
certifying new functionality
7
2
CAN WE MAKE BETTER
USE OF OLD KNOWLEDGE?
• Learning domain ontologies.
• Corpus definition.
• How to revise old knowledge?
• The privileged review problem.
• Transfer learning.
8
3
SUPPORT
Gather case study data
Synthetic studies
Annonymization of data
Training
• Papers
• Tutorials
• Learning information
seeking behavior
9
4
LESS IS MORE
• Reasoning via fewer, most representative
examples
• Active learning
• Early stopping
• Stack ranking (early stop)
10
5

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Lexisnexis june9

  • 2. SEBIG LAB : SE FOR BIG DATA • Three year partnership • New lab to explore SE methods for big data apps. • Grow skill set of engineers: • Assess different approaches to Big Data • Validation of results 2
  • 3. LAB PROCESSES VS INDUSTRIAL PROCESSES • Lab processes • Make 10ml of oxygen? • Easy! • Make 100,000 liters per day? • That’s another matter 3
  • 5. INDUSTRIAL PROCESSES FOR DATA MINING 5 1 23 4 5
  • 6. EXPLORING NEW ALGORITHMS • New ideas • SVM • Deep learning • Ensembles • etc • Visualizations • Parameter tuning • Synonym discovery • Incremental association rule learning 6 1
  • 7. VALIDATION STUDIES • Independent checks of industrial results • Optimizing validation: • ? Mechanical Turk • Better support tools for coding new functionality • Better test suites for certifying new functionality 7 2
  • 8. CAN WE MAKE BETTER USE OF OLD KNOWLEDGE? • Learning domain ontologies. • Corpus definition. • How to revise old knowledge? • The privileged review problem. • Transfer learning. 8 3
  • 9. SUPPORT Gather case study data Synthetic studies Annonymization of data Training • Papers • Tutorials • Learning information seeking behavior 9 4
  • 10. LESS IS MORE • Reasoning via fewer, most representative examples • Active learning • Early stopping • Stack ranking (early stop) 10 5