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» Evaluation of Sampling for Data Mining of Association Rules
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SDM
2007
SIAM
146views Data Mining» more  SDM 2007»
15 years 2 months ago
ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...
191
Voted
VLDB
2008
ACM
147views Database» more  VLDB 2008»
16 years 24 days ago
Providing k-anonymity in data mining
In this paper we present extended definitions of k-anonymity and use them to prove that a given data mining model does not violate the k-anonymity of the individuals represented in...
Arik Friedman, Ran Wolff, Assaf Schuster
222
Voted
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
16 years 1 months ago
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
Barzan Mozafari, Hetal Thakkar, Carlo Zaniolo
KDD
2002
ACM
106views Data Mining» more  KDD 2002»
16 years 1 months ago
Selecting the right interestingness measure for association patterns
Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava
FUIN
2007
109views more  FUIN 2007»
15 years 16 days ago
Unifying Framework for Rule Semantics: Application to Gene Expression Data
Abstract. The notion of rules is very popular and appears in different flavors, for example as association rules in data mining or as functional dependencies in databases. Their s...
Marie Agier, Jean-Marc Petit, Einoshin Suzuki