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ISCI
2008
166views more  ISCI 2008»
15 years 6 months ago
A discretization algorithm based on Class-Attribute Contingency Coefficient
Discretization algorithms have played an important role in data mining and knowledge discovery. They not only produce a concise summarization of continuous attributes to help the ...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
ICDM
2008
IEEE
185views Data Mining» more  ICDM 2008»
16 years 26 days ago
Clustering Uncertain Data Using Voronoi Diagrams
We study the problem of clustering uncertain objects whose locations are described by probability density functions (pdf). We show that the UK-means algorithm, which generalises t...
Ben Kao, Sau Dan Lee, David W. Cheung, Wai-Shing H...
RAID
2010
Springer
15 years 4 months ago
On Challenges in Evaluating Malware Clustering
Malware clustering and classification are important tools that enable analysts to prioritize their malware analysis efforts. The recent emergence of fully automated methods for ma...
Peng Li, Limin Liu, Debin Gao, Michael K. Reiter
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2005
ACM
163views Data Mining» more  KDD 2005»
16 years 6 months ago
Data Sparsity Issues in the Collaborative Filtering Framework
Abstract. With the amount of available information on the Web growing rapidly with each day, the need to automatically filter the information in order to ensure greater user effici...
Miha Grcar, Dunja Mladenic, Blaz Fortuna, Marko Gr...