Over the past two decades, pattern mining techniques have become an integral part of many
bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining …

Page 1 | NTRO DU CT | ON TO DATA MINING PANG - NING TAN MICHAEL STEINBACH V|PIN
KU MAR ALWAYS L EA RN | NG |PEARSON Page 2 |NTRODUCTION TO DA T AM | N | N G …

Association rule mining is one of the fundamental research topics in data mining and
knowledge discovery that identifies interesting relationships between itemsets in datasets …

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life
Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent …

Fault diagnosis within electrical power systems is a time consuming and complex task.
SCADA systems, digital fault recorders, travelling wave fault locators and other monitoring …

Association rule mining research typically focuses on positive association rules (PARs),
generated from frequently occurring itemsets. However, in recent years, there has been a …

Linked open data (LOD), as provided by a quickly growing number of sources constitutes a
wealth of easily accessible information. However, this data is not easy to understand. It is …

This paper is concerned with discovering positive and negative association rules, a problem
which has been addressed by various authors from different angles, but for which no fully …

Different from traditional positive sequential pattern mining, negative sequential pattern
mining considers both positive and negative relationships between items. Negative …

Motivation Modeling microbiome systems as complex networks are known as the problem of
network inference. Microbial association network inference is of great significance in …