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» Mining Very Large Databases
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ADC
2008
Springer
110views Database» more  ADC 2008»
14 years 4 months ago
Graph Mining based on a Data Partitioning Approach
Existing graph mining algorithms typically assume that the dataset can fit into main memory. As many large graph datasets cannot satisfy this condition, truly scalable graph minin...
Son N. Nguyen, Maria E. Orlowska, Xue Li
VLDB
2004
ACM
99views Database» more  VLDB 2004»
14 years 3 months ago
Query Languages and Data Models for Database Sequences and Data Streams
We study the fundamental limitations of relational algebra (RA) and SQL in supporting sequence and stream queries, and present effective query language and data model enrichments ...
Yan-Nei Law, Haixun Wang, Carlo Zaniolo
ICDM
2006
IEEE
161views Data Mining» more  ICDM 2006»
14 years 4 months ago
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets
In many clustering applications for bioinformatics, only part of the data clusters into one or more groups while the rest needs to be pruned. For such situations, we present Hiera...
Gunjan Gupta, Alexander Liu, Joydeep Ghosh
AIR
2000
91views more  AIR 2000»
13 years 9 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
KDD
1995
ACM
67views Data Mining» more  KDD 1995»
14 years 1 months ago
A Perspective on Databases and Data Mining
We discuss the use of database met hods for data mining. Recently impressive results have been achieved for some data mining problems using highly specialized and clever data stru...
Marcel Holsheimer, Martin L. Kersten, Heikki Manni...