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» Discovery of Influence Sets in Frequently Updated Databases
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ICDE
2005
IEEE
133views Database» more  ICDE 2005»
14 years 8 months ago
Efficient Inverted Lists and Query Algorithms for Structured Value Ranking in Update-Intensive Relational Databases
We propose a new ranking paradigm for relational databases called Structured Value Ranking (SVR). SVR uses structured data values to score (rank) the results of keyword search que...
Lin Guo, Jayavel Shanmugasundaram, Kevin S. Beyer,...
JIIS
2010
106views more  JIIS 2010»
13 years 2 months ago
A new classification of datasets for frequent itemsets
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to ...
Frédéric Flouvat, Fabien De Marchi, ...
ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
14 years 1 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
FQAS
2004
Springer
146views Database» more  FQAS 2004»
13 years 11 months ago
Discovering Representative Models in Large Time Series Databases
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Simona E. Rombo, Giorgio Terracina
ADBIS
2000
Springer
111views Database» more  ADBIS 2000»
13 years 11 months ago
Discovering Frequent Episodes in Sequences of Complex Events
Data collected in many applications have a form of sequences of events. One of the popular data mining problems is discovery of frequently occurring episodes in such sequences. Eff...
Marek Wojciechowski