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KDD
2012
ACM
202views Data Mining» more  KDD 2012»
12 years 1 months ago
UFIMT: an uncertain frequent itemset mining toolbox
In recent years, mining frequent itemsets over uncertain data has attracted much attention in the data mining community. Unlike the corresponding problem in deterministic data, th...
Yongxin Tong, Lei Chen 0002, Philip S. Yu
ISMIS
2011
Springer
13 years 2 months ago
Data Access Paths in Processing of Sets of Frequent Itemset Queries
Abstract. Frequent itemset mining can be regarded as advanced database querying where a user specifies the dataset to be mined and constraints to be satisfied by the discovered i...
Piotr Jedrzejczak, Marek Wojciechowski
CORR
2011
Springer
222views Education» more  CORR 2011»
13 years 3 months ago
A New Data Layout For Set Intersection on GPUs
Abstract—Set intersection is the core in a variety of problems, e.g. frequent itemset mining and sparse boolean matrix multiplication. It is well-known that large speed gains can...
Rasmus Resen Amossen, Rasmus Pagh
KAIS
2006
164views more  KAIS 2006»
13 years 11 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
SIGCOMM
2010
ACM
13 years 11 months ago
Automating root-cause analysis of network anomalies using frequent itemset mining
Finding the root-cause of a network security anomaly is essential for network operators. In our recent work [1, 5], we introduced a generic technique that uses frequent itemset mi...
Ignasi Paredes-Oliva, Xenofontas A. Dimitropoulos,...
FIMI
2003
210views Data Mining» more  FIMI 2003»
14 years 24 days ago
COFI-tree Mining: A New Approach to Pattern Growth with Reduced Candidacy Generation
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
Osmar R. Zaïane, Mohammad El-Hajj
FIMI
2003
95views Data Mining» more  FIMI 2003»
14 years 24 days ago
Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets
A simple new algorithm is suggested for frequent itemset mining, using item probabilities as the basis for generating candidates. The method first finds all the frequent items, an...
Attila Gyenesei, Jukka Teuhola
FIMI
2003
88views Data Mining» more  FIMI 2003»
14 years 24 days ago
A fast APRIORI implementation
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...
Ferenc Bodon
FIMI
2004
175views Data Mining» more  FIMI 2004»
14 years 25 days ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan
FIMI
2004
123views Data Mining» more  FIMI 2004»
14 years 25 days ago
Surprising Results of Trie-based FIM Algorithms
Trie is a popular data structure in frequent itemset mining (FIM) algorithms. It is memory-efficient, and allows fast construction and information retrieval. Many trie-related tec...
Ferenc Bodon