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KDD
2002
ACM
140views Data Mining» more  KDD 2002»
16 years 5 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
SIGMOD
2008
ACM
89views Database» more  SIGMOD 2008»
16 years 5 months ago
Towards identity anonymization on graphs
The proliferation of network data in various application domains has raised privacy concerns for the individuals involved. Recent studies show that simply removing the identities ...
Kun Liu, Evimaria Terzi
SIGMOD
2007
ACM
160views Database» more  SIGMOD 2007»
16 years 5 months ago
Supporting ranking and clustering as generalized order-by and group-by
The Boolean semantics of SQL queries cannot adequately capture the "fuzzy" preferences and "soft" criteria required in non-traditional data retrieval applicati...
Chengkai Li, Min Wang, Lipyeow Lim, Haixun Wang, K...
SIGMOD
2006
ACM
238views Database» more  SIGMOD 2006»
16 years 5 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...
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
16 years 2 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
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