1. Christos Faloutsos CMU
SDM’07 Panel Data Mining Research: Current Status and Future Opportunities
Christos Faloutsos
CMU

2. Questions
Q1: What are future challenges and opportunities for data mining that are not presently receiving as much attention as they deserve?
Q2: Are there things we are doing now that we should be rethinking in considering future challenges and opportunities for data mining?
SDM'07
C. Faloutsos, CMU

3. Past + current successes
cross-disciplinarity: DM = Stat, ML, DB
fascinating apps:
Bio-informatics
privacy
security
streams
social network mining
...
SDM'07
C. Faloutsos, CMU

4. Machine Learning to support Systems Biology: Subcellular Location - Bob Murphy
Cell Images of many proteins
Feature Extraction, Graphical Models, Clustering of proteins by pattern
Combine to enable accurate simulation of cell behavior
Generative Models for each pattern
SDM'07
C. Faloutsos, CMU

5. Q1: Challenges to focus on
Scalability – mining Tera and Peta bytes
stream mining (anomaly, intrusion detection, sensors)
graph mining (text/web mining, marketing, ...)
autonomic systems
search engines
national security
...
SDM'07
C. Faloutsos, CMU

6. Scalability
Google: > 450,000 processors in clusters of ~2000 processors each
target: hundreds of Tb, to several Peta-bytes
Barroso, Dean, Hölzle, “Web Search for a Planet: The Google Cluster Architecture” IEEE Micro 2003
SDM'07
C. Faloutsos, CMU

7. E.g.: self-* system @ CMU >200 nodes
40 racks of computing equipment
774kw of power.
target: 1 PetaByte
goal: self-correcting, self-securing, self-monitoring, self-...
PT bytes, self-*, linux, gigabit link?
SDM'07
C. Faloutsos, CMU 7

8. SDM'07
C. Faloutsos, CMU

9. DM for Tera- and Peta-bytes
Two-way street:
<- DM can use such infrastructures to find patterns
-> DM can help such infrastructures become self-healing, self-adjusting, ‘self-*’
SDM'07
C. Faloutsos, CMU

10. Q2: What to do differently
emphasis on Systems – DM collaboration
SDM'07
C. Faloutsos, CMU