Sciweavers

TEC
2008
104views more  TEC 2008»
13 years 5 months ago
Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy
Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data i...
Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-...
CORR
2008
Springer
99views Education» more  CORR 2008»
13 years 5 months ago
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
Michael Hahsler
CORR
2008
Springer
115views Education» more  CORR 2008»
13 years 5 months ago
New probabilistic interest measures for association rules
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for ...
Michael Hahsler, Kurt Hornik
NIPS
2001
13 years 6 months ago
Bayesian Predictive Profiles With Applications to Retail Transaction Data
Massive transaction data sets are recorded in a routine manner in telecommunications, retail commerce, and Web site management. In this paper we address the problem of inferring p...
Igor V. Cadez, Padhraic Smyth
PAKDD
2010
ACM
275views Data Mining» more  PAKDD 2010»
13 years 9 months ago
Anonymizing Transaction Data by Integrating Suppression and Generalization
Abstract. Privacy protection in publishing transaction data is an important problem. A key feature of transaction data is the extreme sparsity, which renders any single technique i...
Junqiang Liu, Ke Wang
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
13 years 11 months ago
Implications of Probabilistic Data Modeling for Mining Association Rules
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. In the current literature, the properties of algorithms to mine ass...
Michael Hahsler, Kurt Hornik, Thomas Reutterer
PAKDD
2007
ACM
144views Data Mining» more  PAKDD 2007»
13 years 11 months ago
Approximately Mining Recently Representative Patterns on Data Streams
Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding windo...
Jia-Ling Koh, Yuan-Bin Don
FUZZIEEE
2007
IEEE
13 years 11 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...
COLCOM
2007
IEEE
13 years 11 months ago
Privacy protection on sliding window of data streams
—In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers that needs to be carefully managed ...
Weiping Wang 0001, Jianzhong Li, Chunyu Ai, Yingsh...
ICDM
2008
IEEE
95views Data Mining» more  ICDM 2008»
13 years 11 months ago
Publishing Sensitive Transactions for Itemset Utility
We consider the problem of publishing sensitive transaction data with privacy preservation. High dimensionality of transaction data poses unique challenges on data privacy and dat...
Yabo Xu, Benjamin C. M. Fung, Ke Wang, Ada Wai-Che...