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DKE
2008
159views more  DKE 2008»
13 years 6 months ago
Isolated items discarding strategy for discovering high utility itemsets
Traditional methods of association rule mining consider the appearance of an item in a transaction, whether or not it is purchased, as a binary variable. However, customers may pu...
Yu-Chiang Li, Jieh-Shan Yeh, Chin-Chen Chang
PKDD
2010
Springer
124views Data Mining» more  PKDD 2010»
13 years 4 months ago
Summarising Data by Clustering Items
Abstract. For a book, the title and abstract provide a good first impression of what to expect from it. For a database, getting a first impression is not so straightforward. Whil...
Michael Mampaey, Jilles Vreeken
ADC
2003
Springer
182views Database» more  ADC 2003»
13 years 11 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
MICCAI
2010
Springer
13 years 4 months ago
Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
ADMA
2008
Springer
114views Data Mining» more  ADMA 2008»
14 years 19 days ago
Using Data Mining Methods to Predict Personally Identifiable Information in Emails
Private information management and compliance are important issues nowadays for most of organizations. As a major communication tool for organizations, email is one of the many pot...
Liqiang Geng, Larry Korba, Xin Wang, Yunli Wang, H...