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ICDE
2000
IEEE
96views Database» more  ICDE 2000»
14 years 8 months ago
Dynamic Miss-Counting Algorithms: Finding Implication and Similarity Rules with Confidence Pruning
Dynamic Miss-Countingalgorithms are proposed, which find all implication and similarity rules with confidence pruning but without support pruning. To handle data sets with a large...
Shinji Fujiwara, Jeffrey D. Ullman, Rajeev Motwani
SSDBM
2005
IEEE
122views Database» more  SSDBM 2005»
14 years 1 months ago
Detection and Tracking of Discrete Phenomena in Sensor-Network Databases
This paper introduces a framework for Phenomena Detection and Tracking (PDT, for short) in sensor network databases. Examples of detectable phenomena include the propagation over ...
Mohamed H. Ali, Mohamed F. Mokbel, Walid G. Aref, ...
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
13 years 7 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
ICDE
2006
IEEE
183views Database» more  ICDE 2006»
14 years 1 months ago
Similarity Queries on Structured Data in Structured Overlays
Structured P2P systems based on distributed hash tables are a popular choice for building large-scaled data management systems. Generally, they only support exact match queries, b...
Marcel Karnstedt, Kai-Uwe Sattler, Manfred Hauswir...
JMLR
2008
148views more  JMLR 2008»
13 years 7 months ago
Linear-Time Computation of Similarity Measures for Sequential Data
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
Konrad Rieck, Pavel Laskov