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SIGMOD
2006
ACM
238views Database» more  SIGMOD 2006»
14 years 8 months ago
Continuous monitoring of top-k queries over sliding windows
Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in convent...
Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Pa...
IDA
2002
Springer
13 years 8 months ago
Online classification of nonstationary data streams
Most classification methods are based on the assumption that the data conforms to a stationary distribution. However, the real-world data is usually collected over certain periods...
Mark Last
ICDE
2007
IEEE
143views Database» more  ICDE 2007»
14 years 10 months ago
Hiding in the Crowd: Privacy Preservation on Evolving Streams through Correlation Tracking
We address the problem of preserving privacy in streams, which has received surprisingly limited attention. For static data, a well-studied and widely used approach is based on ra...
Feifei Li, Jimeng Sun, Spiros Papadimitriou, Georg...
ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
14 years 2 months ago
An Algorithm for In-Core Frequent Itemset Mining on Streaming Data
Frequent itemset mining is a core data mining operation and has been extensively studied over the last decade. This paper takes a new approach for this problem and makes two major...
Ruoming Jin, Gagan Agrawal
DASFAA
2010
IEEE
193views Database» more  DASFAA 2010»
13 years 6 months ago
A Simple, Yet Effective and Efficient, Sliding Window Sampling Algorithm
Sampling streams of continuous data with limited memory, or reservoir sampling, is a utility algorithm. Standard reservoir sampling maintains a random sample of the entire stream a...
Xuesong Lu, Wee Hyong Tok, Chedy Raïssi, St&e...