The main purpose of data mining and analytics is to find novel, potentially useful patterns
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …

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 …

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

Mining information and knowledge from large databases has been recognized by many
researchers as a key research topic in database systems and machine learning, and by …

Most statistical and machine-learning algorithms assume that the data is a random sample
drawn from a stationary distribution. Unfortunately, most of the large databases available for …

Frequent pattern mining has been a focused theme in data mining research for over a
decade. Abundant literature has been dedicated to this research and tremendous progress …

This paper proposes a novel approach named AGM to efficiently mine the association rules
among the frequently appearing sub-structures in a given graph data set. A graph …

During decision making, we are often confronted by a huge amount of factors. These factors
may be either an advantage or a disadvantage to a decision objective. For the purpose of …

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 …

On a data warehouse, either manual analyses supported by appropriate visualization tools
or (semi-) automatic data mining may be performed, eg clustering, classification and …