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» On compressing frequent patterns
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151
Voted
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
16 years 4 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
150
Voted
SIGMOD
2004
ACM
162views Database» more  SIGMOD 2004»
16 years 3 months ago
Graph Indexing: A Frequent Structure-based Approach
Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is...
Xifeng Yan, Philip S. Yu, Jiawei Han
233
Voted
PODS
2009
ACM
134views Database» more  PODS 2009»
16 years 4 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
154
Voted
TKDE
2008
153views more  TKDE 2008»
15 years 3 months ago
Discovering Frequent Agreement Subtrees from Phylogenetic Data
We study a new data mining problem concerning the discovery of frequent agreement subtrees (FASTs) from a set of phylogenetic trees. A phylogenetic tree, or phylogeny, is an unorde...
Sen Zhang, Jason Tsong-Li Wang
113
Voted
KDD
2003
ACM
124views Data Mining» more  KDD 2003»
16 years 4 months ago
Information-theoretic co-clustering
Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingenc...
Inderjit S. Dhillon, Subramanyam Mallela, Dharmend...