265 search results - page 27 / 53 » Approximation algorithms for clustering uncertain data |
STACS
2007
Springer
14 years 1 months ago
2007
Springer
The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
PODS
2003
ACM
14 years 7 months ago
2003
ACM
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
EDBT
2004
ACM
14 years 7 months ago
2004
ACM
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
ACSAC
2001
IEEE
13 years 11 months ago
2001
IEEE
It is a well-known problem that intrusion detection systems overload their human operators by triggering thousands of alarms per day. As a matter of fact, we have been asked by on...
CSB
2005
IEEE
14 years 1 months ago
2005
IEEE
This work presents the development of algorithms for approximate string matching using parallel methods. It intends to do the maximum of molecular sequences comparisons per unity ...