This paper presents the top 10 data mining algorithms identified by the IEEE International
Conference on Data Mining (ICDM) in December 2006: C4. 5, k-Means, SVM, Apriori, EM …

A motion object extraction algorithm based on the active contour model is proposed. Firstly,
moving areas involving shadows are segmented with the classical background difference …

For a transaction database, a frequent itemset is an itemset included in at least a specified
number of transactions. A frequent itemset P is maximal if P is included in no other frequent …

For a transaction database, a frequent itemset is an itemset included in at least a specified
number of transactions. To find all the frequent itemsets, the heaviest task is the computation …

In this chapter, we introduce Formal Concept Analysis (FCA) and some of its extensions.
FCA is a formalism based on lattice theory aimed at data analysis and knowledge …

In contrast to frequent itemset mining (FIM) algorithms that focus on identifying itemsets with
high occurrence frequency, high-utility itemset mining algorithms can reveal the most …

We present several exact and highly scalable local pattern sampling algorithms. They can
be used as an alternative to exhaustive local pattern discovery methods (eg, frequent set …

Frequent closed itemsets (FCI) play an important role in pruning redundant rules fast.
Therefore, a lot of algorithms for mining FCI have been developed. Algorithms based on …

We present a novel algorithm for significant pattern mining, Westfall-Young light. The target
patterns are statistically significantly enriched in one of two classes of objects. Our method …

The extraction of patterns displaying significant association with a class label is a key data
mining task with wide application in many domains. We study a variant of the problem that …