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ADMA
2006
Springer
137views Data Mining» more  ADMA 2006»
15 years 9 months ago
SA-IFIM: Incrementally Mining Frequent Itemsets in Update Distorted Databases
Abstract. The issue of maintaining privacy in frequent itemset mining has attracted considerable attentions. In most of those works, only distorted data are available which may bri...
Jinlong Wang, Congfu Xu, Hongwei Dan, Yunhe Pan
EUSFLAT
2009
233views Fuzzy Logic» more  EUSFLAT 2009»
15 years 3 months ago
SaM: A Split and Merge Algorithm for Fuzzy Frequent Item Set Mining
This paper presents SaM, a split and merge algorithm for frequent item set mining. Its distinguishing qualities are an exceptionally simple algorithm and data structure, which not ...
Christian Borgelt, Xiaomeng Wang
ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
15 years 11 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 6 months ago
Collusion-resistant anonymous data collection method
The availability and the accuracy of the data dictate the success of a data mining application. Increasingly, there is a need to resort to on-line data collection to address the p...
Mafruz Zaman Ashrafi, See-Kiong Ng
146
Voted
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 6 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman