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PAKDD
2010
ACM
169views Data Mining» more  PAKDD 2010»
15 years 9 months ago
oddball: Spotting Anomalies in Weighted Graphs
Given a large, weighted graph, how can we find anomalies? Which rules should be violated, before we label a node as an anomaly? We propose the OddBall algorithm, to find such nod...
Leman Akoglu, Mary McGlohon, Christos Faloutsos
KDD
2002
ACM
109views Data Mining» more  KDD 2002»
16 years 5 months ago
Mining intrusion detection alarms for actionable knowledge
In response to attacks against enterprise networks, administrators increasingly deploy intrusion detection systems. These systems monitor hosts, networks, and other resources for ...
Klaus Julisch, Marc Dacier
125
Voted
EEE
2004
IEEE
15 years 8 months ago
Mining Traveling and Purchasing Behaviors of Customers in Electronic Commerce Environment
Web usage mining is the process of extracting interesting patterns from web logs. This paper proposes an IPA (Integrating Path traversal patterns and Association rules) model for ...
Yue-Shi Lee, Show-Jane Yen, Ghi-Hua Tu, Min-Chi Hs...
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 5 months ago
V-Miner: using enhanced parallel coordinates to mine product design and test data
Analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. This paper proposes a new technique based on parallel coordi...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
MLDM
2007
Springer
15 years 11 months ago
Mining Frequent Trajectories of Moving Objects for Location Prediction
Advances in wireless and mobile technology flood us with amounts of moving object data that preclude all means of manual data processing. The volume of data gathered from position...
Mikolaj Morzy