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» A New Algorithm for Mining Sequential Patterns
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KDD
2004
ACM
207views Data Mining» more  KDD 2004»
14 years 8 months ago
SPIN: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Jun Huan, Wei Wang 0010, Jan Prins, Jiong Yang
ICDE
2009
IEEE
173views Database» more  ICDE 2009»
13 years 5 months ago
Efficient Mining of Closed Repetitive Gapped Subsequences from a Sequence Database
There is a huge wealth of sequence data available, for example, customer purchase histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of data to ...
Bolin Ding, David Lo, Jiawei Han, Siau-Cheng Khoo
CORR
2012
Springer
202views Education» more  CORR 2012»
12 years 3 months ago
Mining Flipping Correlations from Large Datasets with Taxonomies
In this paper we introduce a new type of pattern – a flipping correlation pattern. The flipping patterns are obtained from contrasting the correlations between items at diffe...
Marina Barsky, Sangkyum Kim, Tim Weninger, Jiawei ...
KDD
2005
ACM
151views Data Mining» more  KDD 2005»
14 years 8 months ago
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
Qiaozhu Mei, ChengXiang Zhai
KDD
1998
ACM
212views Data Mining» more  KDD 1998»
13 years 11 months ago
Learning to Predict Rare Events in Event Sequences
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Gary M. Weiss, Haym Hirsh