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» Mining Rare Association Rules from e-Learning Data
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KDD
2007
ACM
566views Data Mining» more  KDD 2007»
14 years 7 months ago
IMDS: intelligent malware detection system
The proliferation of malware has presented a serious threat to the security of computer systems. Traditional signature-based antivirus systems fail to detect polymorphic and new, ...
Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye
ASUNAM
2009
IEEE
14 years 2 months ago
Modeling a Store's Product Space as a Social Network
A market basket is a set of products that form a single retail transaction. This purchase data of products can shed important light on how product(s) might influence sales of oth...
Troy Raeder, Nitesh V. Chawla
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
14 years 7 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
RCIS
2010
13 years 5 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
ICDE
2009
IEEE
1081views Database» more  ICDE 2009»
15 years 7 months ago
Modeling and Integrating Background Knowledge in Data Anonymization
Recent work has shown the importance of considering the adversary’s background knowledge when reasoning about privacy in data publishing. However, it is very difficult for the d...
Tiancheng Li, Ninghui Li, Jian Zhang