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» Clustering Improves the Exploration of Graph Mining Results
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KDD
2005
ACM
151views Data Mining» more  KDD 2005»
14 years 7 months ago
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
Qiaozhu Mei, ChengXiang Zhai
GECCO
2005
Springer
134views Optimization» more  GECCO 2005»
14 years 28 days ago
Predicting mining activity with parallel genetic algorithms
We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa ...
Sam Talaie, Ryan E. Leigh, Sushil J. Louis, Gary L...
PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 5 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
DIS
2009
Springer
14 years 2 months ago
Mining Heterogeneous Information Networks by Exploring the Power of Links
Knowledge is power but for interrelated data, knowledge is often hidden in massive links in heterogeneous information networks. We explore the power of links at mining heterogeneou...
Jiawei Han
ACSAC
2001
IEEE
13 years 11 months ago
Mining Alarm Clusters to Improve Alarm Handling Efficiency
It is a well-known problem that intrusion detection systems overload their human operators by triggering thousands of alarms per day. As a matter of fact, we have been asked by on...
Klaus Julisch