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ICDM
2008
IEEE
123views Data Mining» more  ICDM 2008»
13 years 11 months ago
Discovering Flow Anomalies: A SWEET Approach
Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fractio...
James M. Kang, Shashi Shekhar, Christine Wennen, P...
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
13 years 11 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
ICDM
2008
IEEE
401views Data Mining» more  ICDM 2008»
13 years 11 months ago
Graph OLAP: Towards Online Analytical Processing on Graphs
OLAP (On-Line Analytical Processing) is an important notion in data analysis. Recently, more and more graph or networked data sources come into being. There exists a similar need ...
Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han, Phil...
ICDM
2008
IEEE
155views Data Mining» more  ICDM 2008»
13 years 11 months ago
Organic Pie Charts
We present a new visualization of the distance and cluster structure of high dimensional data. It is particularly well suited for analysis tasks of users unfamiliar with complex d...
Fabian Mörchen
ICDM
2008
IEEE
128views Data Mining» more  ICDM 2008»
13 years 11 months ago
Cost-Sensitive Parsimonious Linear Regression
We examine linear regression problems where some features may only be observable at a cost (e.g., in medical domains where features may correspond to diagnostic tests that take ti...
Robby Goetschalckx, Kurt Driessens, Scott Sanner
ICDM
2008
IEEE
172views Data Mining» more  ICDM 2008»
13 years 11 months ago
Latent Dirichlet Allocation and Singular Value Decomposition Based Multi-document Summarization
Multi-Document Summarization deals with computing a summary for a set of related articles such that they give the user a general view about the events. One of the objectives is th...
Rachit Arora, Balaraman Ravindran
ICDM
2008
IEEE
112views Data Mining» more  ICDM 2008»
13 years 11 months ago
Supervised Inductive Learning with Lotka-Volterra Derived Models
We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists ...
Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
ICDM
2008
IEEE
96views Data Mining» more  ICDM 2008»
13 years 11 months ago
Filling in the Blanks - Krimp Minimisation for Missing Data
Many data sets are incomplete. For correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. Imputation has the bene...
Jilles Vreeken, Arno Siebes
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
13 years 11 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
ICDM
2008
IEEE
90views Data Mining» more  ICDM 2008»
13 years 11 months ago
Finding Alternative Clusterings Using Constraints
1 The aim of data mining is to find novel and actionable insights. However, most algorithms typically just find a single explanation of the data even though alternatives could e...
Ian Davidson, Zijie Qi