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ICDM
2010
IEEE
108views Data Mining» more  ICDM 2010»
13 years 8 months ago
Assessing Data Mining Results on Matrices with Randomization
Abstract--Randomization is a general technique for evaluating the significance of data analysis results. In randomizationbased significance testing, a result is considered to be in...
Markus Ojala
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
13 years 8 months ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar
ICDM
2010
IEEE
111views Data Mining» more  ICDM 2010»
13 years 8 months ago
ValuePick: Towards a Value-Oriented Dual-Goal Recommender System
Given a user in a social network, which new friends should we recommend, the dual goal being to achieve user satisfaction and good network connectivity? Similarly, which new produc...
Leman Akoglu, Christos Faloutsos
ICDM
2010
IEEE
212views Data Mining» more  ICDM 2010»
13 years 8 months ago
Modeling Information Diffusion in Implicit Networks
Social media forms a central domain for the production and dissemination of real-time information. Even though such flows of information have traditionally been thought of as diffu...
Jaewon Yang, Jure Leskovec
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
13 years 8 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim