Mining significant graph patterns by leap search
With ever-increasing amounts of graph data from disparate sources, there has been a strong
need for exploiting significant graph patterns with user-specified objective functions. Most …
need for exploiting significant graph patterns with user-specified objective functions. Most …
Coversize: A global constraint for frequency-based itemset mining
Constraint Programming is becoming competitive for solving certain data-mining problems
largely due to the development of global constraints. We introduce the CoverSize constraint …
largely due to the development of global constraints. We introduce the CoverSize constraint …
The chosen few: On identifying valuable patterns
B Bringmann, A Zimmermann - Seventh IEEE International …, 2007 - ieeexplore.ieee.org
Constrained pattern mining extracts patterns based on their individual merit. Usually this
results in far more patterns than a human expert or a machine learning technique could …
results in far more patterns than a human expert or a machine learning technique could …
Correlated itemset mining in ROC space: a constraint programming approach
Correlated or discriminative pattern mining is concerned with finding the highest scoring
patterns wrt a correlation measure (such as information gain). By reinterpreting correlation …
patterns wrt a correlation measure (such as information gain). By reinterpreting correlation …
Pattern-based classification: A unifying perspective
The use of patterns in predictive models is a topic that has received a lot of attention in
recent years. Pattern mining can help to obtain models for structured domains, such as …
recent years. Pattern mining can help to obtain models for structured domains, such as …
Cluster-grouping: from subgroup discovery to clustering
A Zimmermann, L De Raedt - Machine Learning, 2009 - Springer
We introduce the problem of cluster-grouping and show that it can be considered a subtask
in several important data mining tasks, such as subgroup discovery, mining correlated …
in several important data mining tasks, such as subgroup discovery, mining correlated …
Supervised pattern mining and applications to classification
A Zimmermann, S Nijssen - Frequent pattern mining, 2014 - Springer
In this chapter we describe the use of patterns in the analysis of supervised data. We survey
the different settings for finding patterns as well as sets of patterns. The pattern mining …
the different settings for finding patterns as well as sets of patterns. The pattern mining …
Authorship classification: a discriminative syntactic tree mining approach
In the past, there have been dozens of studies on automatic authorship classification, and
many of these studies concluded that the writing style is one of the best indicators for original …
many of these studies concluded that the writing style is one of the best indicators for original …
One in a million: picking the right patterns
B Bringmann, A Zimmermann - Knowledge and Information Systems, 2009 - Springer
Constrained pattern mining extracts patterns based on their individual merit. Usually this
results in far more patterns than a human expert or a machine leaning technique could make …
results in far more patterns than a human expert or a machine leaning technique could make …
Data centric cache measurement on the Intel ltanium 2 processor
BR Buck, JK Hollingsworth - SC'04: Proceedings of the 2004 …, 2004 - ieeexplore.ieee.org
Processor speed continues to increase faster than the speed of access to main memory,
making effective use of memory caches more important. Information about an application's …
making effective use of memory caches more important. Information about an application's …