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VLDB
1998
ACM
112views Database» more  VLDB 1998»
14 years 2 months ago
Incremental Clustering for Mining in a Data Warehousing Environment
Data warehouses provide a great deal of opportunities for performing data mining tasks such as classification and clustering. Typically, updates are collected and applied to the d...
Martin Ester, Hans-Peter Kriegel, Jörg Sander...
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 3 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
AIR
2000
91views more  AIR 2000»
13 years 10 months ago
PlanMine: Predicting Plan Failures Using Sequence Mining
This paper presents the PLANMINE sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because p...
Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara
IPPS
2006
IEEE
14 years 4 months ago
Supporting self-adaptation in streaming data mining applications
There are many application classes where the users are flexible with respect to the output quality. At the same time, there are other constraints, such as the need for real-time ...
Liang Chen, Gagan Agrawal
ICDM
2009
IEEE
133views Data Mining» more  ICDM 2009»
13 years 7 months ago
Pattern Mining over Star Schemas in the Onto4AR Framework
Storing data according to the multidimensional model, in particular following star schemas, has demonstrated to be one of the most adequate forms to ease the exploration of data. ...
Cláudia Antunes