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» Methods for finding frequent items in data streams
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SIGMOD
2005
ACM
150views Database» more  SIGMOD 2005»
14 years 7 months ago
BRAID: Stream Mining through Group Lag Correlations
The goal is to monitor multiple numerical streams, and determine which pairs are correlated with lags, as well as the value of each such lag. Lag correlations (and anticorrelation...
Yasushi Sakurai, Spiros Papadimitriou, Christos Fa...
CORR
2010
Springer
90views Education» more  CORR 2010»
13 years 5 months ago
Fast Pseudo-Random Fingerprints
Abstract. We propose a method to exponentially speed up computation of various fingerprints, such as the ones used to compute similarity and rarity in massive data sets. Rather the...
Yoram Bachrach, Ely Porat
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
14 years 14 days ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...
TIME
2008
IEEE
14 years 2 months ago
Time Aware Mining of Itemsets
Frequent behavioural pattern mining is a very important topic of knowledge discovery, intended to extract correlations between items recorded in large databases or Web acces logs....
Bashar Saleh, Florent Masseglia
DKE
2007
153views more  DKE 2007»
13 years 7 months ago
Adaptive similarity search in streaming time series with sliding windows
The challenge in a database of evolving time series is to provide efficient algorithms and access methods for query processing, taking into consideration the fact that the databas...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...