Knowledge Discovery from Data (TKDD)


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ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 4 Issue 2, May 2010

CSNL: A cost-sensitive non-linear decision tree algorithm
Sunil Vadera
Article No.: 6
DOI: 10.1145/1754428.1754429

This article presents a new decision tree learning algorithm called CSNL that induces Cost-Sensitive Non-Linear decision trees. The algorithm is based on the hypothesis that nonlinear decision nodes provide a better...

Analyzing knowledge communities using foreground and background clusters
Vasileios Kandylas, S. Phineas Upham, Lyle H. Ungar
Article No.: 7
DOI: 10.1145/1754428.1754430

Insight into the growth (or shrinkage) of “knowledge communities” of authors that build on each other's work can be gained by studying the evolution over time of clusters of documents. We cluster documents based on the documents they...

A shared-subspace learning framework for multi-label classification
Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye
Article No.: 8
DOI: 10.1145/1754428.1754431

Multi-label problems arise in various domains such as multi-topic document categorization, protein function prediction, and automatic image annotation. One natural way to deal with such problems is to construct a binary classifier for each label,...

Data mining for discrimination discovery
Salvatore Ruggieri, Dino Pedreschi, Franco Turini
Article No.: 9
DOI: 10.1145/1754428.1754432

In the context of civil rights law, discrimination refers to unfair or unequal treatment of people based on membership to a category or a minority, without regard to individual merit. Discrimination in credit, mortgage, insurance, labor market,...