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» Multi-Dimensional Relational Sequence Mining
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BMCBI
2005
152views more  BMCBI 2005»
14 years 11 months ago
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments
Background: The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support ...
S. A. Kirov, X. Peng, E. Baker, D. Schmoyer, B. Zh...
JCP
2006
173views more  JCP 2006»
14 years 11 months ago
Database Intrusion Detection using Weighted Sequence Mining
Data mining is widely used to identify interesting, potentially useful and understandable patterns from a large data repository. With many organizations focusing on webbased on-lin...
Abhinav Srivastava, Shamik Sural, Arun K. Majumdar
IJCSA
2006
138views more  IJCSA 2006»
14 years 11 months ago
An Integrated System for Cancer-Related Genes Mining from Biomedical Literatures
According to statistics, the rate of having cancer is relatively high for people in developing and developed countries. So cancer can be called as the enemy of human health. With ...
Shih-Nung Chen, Kuo-Cheng Wen
SAC
2004
ACM
15 years 5 months ago
A new algorithm for gap constrained sequence mining
The sequence mining problem consists in finding frequent sequential patterns in a database of time-stamped events. Several application domains require limiting the maximum tempor...
Salvatore Orlando, Raffaele Perego, Claudio Silves...
MLDM
2007
Springer
15 years 5 months ago
Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems
In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM...
Trevor Parsons, John Murphy, Patrick O'Sullivan