Fast algorithm for computing fixpoints of Galois connections induced by object-attribute relational data
J Outrata, V Vychodil - Information Sciences, 2012 - Elsevier
Fixpoints of Galois connections induced by object-attribute data tables represent important
patterns that can be found in relational data. Such patterns are used in several data mining …
patterns that can be found in relational data. Such patterns are used in several data mining …
Generalized association rule mining with constraints
Generalized association rule extraction is a powerful tool to discover a high level view of the
interesting patterns hidden in the analyzed data. However, since the patterns are extracted …
interesting patterns hidden in the analyzed data. However, since the patterns are extracted …
PMBC: Pattern mining from biological sequences with wildcard constraints
Patterns/subsequences frequently appearing in sequences provide essential knowledge for
domain experts, such as molecular biologists, to discover rules or patterns hidden behind …
domain experts, such as molecular biologists, to discover rules or patterns hidden behind …
A framework for mining interesting high utility patterns with a strong frequency affinity
High utility pattern (HUP) mining is one of the most important research issues in data mining.
Although HUP mining extracts important knowledge from databases, it requires long …
Although HUP mining extracts important knowledge from databases, it requires long …
Association rule mining algorithms on high-dimensional datasets
D Ai, H Pan, X Li, Y Gao, D He - Artificial Life and Robotics, 2018 - Springer
The science of bioinformatics has been accelerating at a fast pace, introducing more
features and handling bigger volumes. However, these swift changes have, at the same …
features and handling bigger volumes. However, these swift changes have, at the same …
Efficient discovery of sequence outlier patterns
Modern Internet of Things (IoT) applications generate massive amounts of time-stamped
data, much of it in the form of discrete, symbolic sequences. In this work, we present a new …
data, much of it in the form of discrete, symbolic sequences. In this work, we present a new …
Moving microbiota research toward establishing causal associations that represent viable targets for effective public health interventions
V Mai, M Prosperi, L Yaghjyan - Annals of epidemiology, 2016 - Elsevier
Purpose There appears to be great promise in developing targeted interventions that exploit
the complex interactions between commensal microbiota colonizing various anatomic sites …
the complex interactions between commensal microbiota colonizing various anatomic sites …
Closed frequent similar pattern mining: Reducing the number of frequent similar patterns without information loss
AY Rodríguez-González, F Lezama… - Expert Systems with …, 2018 - Elsevier
Frequent pattern mining is considered a key task to discover useful information. Despite the
quality of solutions given by frequent pattern mining algorithms, most of them face the …
quality of solutions given by frequent pattern mining algorithms, most of them face the …
Looking for a structural characterization of the sparseness measure of (frequent closed) itemset contexts
It is widely recognized that the performances of frequent-pattern mining algorithms are
closely dependent on data being handled, ie, sparse or dense. The same situation applies …
closely dependent on data being handled, ie, sparse or dense. The same situation applies …
An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets
MK Vanahalli, N Patil - Information Sciences, 2019 - Elsevier
Mining colossal itemsets from high dimensional datasets have gained focus in recent times.
The conventional algorithms expend most of the time in mining small and mid-sized …
The conventional algorithms expend most of the time in mining small and mid-sized …