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» Intrusion Detection Based on Data Mining
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BPM
2009
Springer
157views Business» more  BPM 2009»
15 years 27 days ago
ProM: The Process Mining Toolkit
Nowadays, all kinds of information systems store detailed information in logs. Examples of such systems include classical workflow management systems (Staffware), ERP systems (SAP)...
Wil M. P. van der Aalst, Boudewijn F. van Dongen, ...
BMCBI
2007
147views more  BMCBI 2007»
14 years 12 months ago
Predicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule mining
Background: Cis-acting transcriptional regulatory elements in mammalian genomes typically contain specific combinations of binding sites for various transcription factors. Althoug...
Xochitl C. Morgan, Shulin Ni, Daniel P. Miranker, ...
AUSDM
2008
Springer
237views Data Mining» more  AUSDM 2008»
15 years 1 months ago
On Inconsistencies in Quantifying Strength of Community Structures
Complex network analysis involves the study of the properties of various real world networks. In this broad field, research on community structures forms an important sub area. Th...
Wen Haw Chong
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
16 years 5 days ago
Belief state approaches to signaling alarms in surveillance systems
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detecti...
Kaustav Das, Andrew W. Moore, Jeff G. Schneider
CIKM
2010
Springer
14 years 10 months ago
SHRINK: a structural clustering algorithm for detecting hierarchical communities in networks
Community detection is an important task for mining the structure and function of complex networks. Generally, there are several different kinds of nodes in a network which are c...
Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, ...