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» Introduction to Data Mining and Knowledge Discovery
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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 7 months ago
Relational data pre-processing techniques for improved securities fraud detection
Commercial datasets are often large, relational, and dynamic. They contain many records of people, places, things, events and their interactions over time. Such datasets are rarel...
Andrew Fast, Lisa Friedland, Marc Maier, Brian Tay...
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
14 years 7 months ago
A visual-analytic toolkit for dynamic interaction graphs
In this article we describe a visual-analytic tool for the interrogation of evolving interaction network data such as those found in social, bibliometric, WWW and biological appli...
Xintian Yang, Sitaram Asur, Srinivasan Parthasarat...
KDD
2009
ACM
204views Data Mining» more  KDD 2009»
14 years 8 months ago
Improving classification accuracy using automatically extracted training data
Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...
ICTAI
2007
IEEE
14 years 1 months ago
A Probabilistic Substructure-Based Approach for Graph Classification
The classification of graph based objects is an important challenge from a knowledge discovery standpoint and has attracted considerable attention recently. In this paper, we pres...
H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jam...
ISCI
2008
166views more  ISCI 2008»
13 years 7 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