20TH ANNIVERSARY COLLOQUIUM SERIES
         Computer Science Department, Boston University

Speaker: Prof. Christos Falutsos
         Carnegie-Mellon University

Title: Data Mining using Fractals and Power Laws

Date:  January 31, 2005
Time:  11am
Place: SAR 102 
       (Sargent college, 635 Commonwealth Ave., building 28 
       on http://www.bu.edu/visit/maps/campus/21-32.html)

Abstract:

What patterns can we find in a bursty web traffic?   On  the
web   or   on  the  internet  graph  itself?   How about the
distributions of galaxies in the sky, or the distribution of
a   company's  customers   in  geographical space?  How long
should we expect a nearest-neighbor  search  to  take,  when
there  are  100 attributes  per  patient or customer record?
The  traditional  assumptions   (uniformity,   independence,
Poisson   arrivals,  Gaussian  distributions),  often  fail.
Should we give up trying to find patterns in such settings?

Self-similarity,  fractals  and  power  laws  are  extremely
successful  in describing real datasets (coast-lines, rivers
basins,  stock-prices,  brain-surfaces,   communication-line
noise,  to name a few).  We show some old and new successes,
involving modeling of graph topologies  (internet,  web  and
social   networks);   modeling   galaxy   and   video  data;
dimensionality reduction; and more.

Brief biography:

Christos Faloutsos holds a Ph.D. degree in Computer  Science
from  the  University of Toronto, Canada.  He is currently a
professor at Carnegie Mellon University.   He  has  received
the  Presidential  Young  Investigator Award by the National
Science Foundation (1989), five ``best paper''  awards,  and
four  teaching  awards.   He has published over 130 refereed
articles,  one  monograph,  and  holds  five  patents.   His
research  interests  include data mining, fractals, indexing
in  relational  and  multimedia  databases,   and   database
performance.

See www-2.cs.cmu.edu/~christos

Host: George Kollios