A primer to frequent itemset mining for bioinformatics
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 …
bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining …
[图书][B] Introduction to data 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 …
KU MAR ALWAYS L EA RN | NG |PEARSON Page 2 |NTRODUCTION TO DA T AM | N | N G …
Fundamentals of association rules in data mining and knowledge discovery
Association rule mining is one of the fundamental research topics in data mining and
knowledge discovery that identifies interesting relationships between itemsets in datasets …
knowledge discovery that identifies interesting relationships between itemsets in datasets …
[图书][B] Contrast data mining: concepts, algorithms, and applications
A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life
Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent …
Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent …
Automating power system fault diagnosis through multi-agent system technology
SDJ McArthur, EM Davidson… - 37th Annual Hawaii …, 2004 - ieeexplore.ieee.org
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 …
SCADA systems, digital fault recorders, travelling wave fault locators and other monitoring …
Negative and positive association rules mining from text using frequent and infrequent itemsets
Association rule mining research typically focuses on positive association rules (PARs),
generated from frequently occurring itemsets. However, in recent years, there has been a …
generated from frequently occurring itemsets. However, in recent years, there has been a …
Profiling linked open data with ProLOD
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 …
wealth of easily accessible information. However, this data is not easy to understand. It is …
Mining positive and negative association rules from large databases
C Cornelis, P Yan, X Zhang… - 2006 IEEE Conference on …, 2006 - ieeexplore.ieee.org
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 …
which has been addressed by various authors from different angles, but for which no fully …
Negative-GSP: An efficient method for mining negative sequential patterns
Different from traditional positive sequential pattern mining, negative sequential pattern
mining considers both positive and negative relationships between items. Negative …
mining considers both positive and negative relationships between items. Negative …
MANIEA: a microbial association network inference method based on improved Eclat association rule mining algorithm
M Liu, Y Ye, J Jiang, K Yang - Bioinformatics, 2021 - academic.oup.com
Motivation Modeling microbiome systems as complex networks are known as the problem of
network inference. Microbial association network inference is of great significance in …
network inference. Microbial association network inference is of great significance in …