Frequent itemset mining: A 25 years review
JM Luna, P Fournier‐Viger… - … Reviews: Data Mining …, 2019 - Wiley Online Library
Frequent itemset mining (FIM) is an essential task within data analysis since it is responsible
for extracting frequently occurring events, patterns, or items in data. Insights from such …
for extracting frequently occurring events, patterns, or items in data. Insights from such …
Using artificial intelligence techniques for COVID-19 genome analysis
The genome of the novel coronavirus (COVID-19) disease was first sequenced in January
2020, approximately a month after its emergence in Wuhan, capital of Hubei province …
2020, approximately a month after its emergence in Wuhan, capital of Hubei province …
MalSPM: Metamorphic malware behavior analysis and classification using sequential pattern mining
Malware pose a serious threat to the computers of individuals, enterprises and other
organizations. In the Windows operating system (OS), Application Programming Interface …
organizations. In the Windows operating system (OS), Application Programming Interface …
[HTML][HTML] Monitoring of student learning in learning management systems: An application of educational data mining techniques
MC Sáiz-Manzanares, JJ Rodríguez-Díez… - Applied Sciences, 2021 - mdpi.com
Featured Application This work has an important direct application for teachers or
educational institutions working with Moodle, because it provides an open access software …
educational institutions working with Moodle, because it provides an open access software …
Packer classification based on association rule mining
Detecting packer programs is a key step in the defense against malicious programs and
plays a key role in cyber security defenses. One challenge with packer classification is that …
plays a key role in cyber security defenses. One challenge with packer classification is that …
Analysis and classification of employee attrition and absenteeism in industry: A sequential pattern mining-based methodology
Employee attrition and absenteeism are major problems that affect many industries and
organizations, resulting in diminished productivity, elevated costs, and losses. These …
organizations, resulting in diminished productivity, elevated costs, and losses. These …
PSAC-PDB: Analysis and classification of protein structures
This paper presents a novel framework, called PSAC-PDB, for analyzing and classifying
protein structures from the Protein Data Bank (PDB). PSAC-PDB first finds, analyze and …
protein structures from the Protein Data Bank (PDB). PSAC-PDB first finds, analyze and …
Using alignment-free and pattern mining methods for SARS-CoV-2 genome analysis
Examining the genome sequences of the SARS-CoV-2 virus, that causes the respiratory
disease known as coronavirus disease 2019 (COVID-19), play important role in the proper …
disease known as coronavirus disease 2019 (COVID-19), play important role in the proper …
VLSD—An efficient subgroup discovery algorithm based on equivalence classes and optimistic estimate
Subgroup Discovery (SD) is a supervised data mining technique for identifying a set of
relations (subgroups) among attributes from a dataset with respect to a target attribute. Two …
relations (subgroups) among attributes from a dataset with respect to a target attribute. Two …
[HTML][HTML] A contrast set mining based approach for cancer subtype analysis
The task of detecting common and unique characteristics among different cancer subtypes is
an important focus of research that aims to improve personalized therapies. Unlike current …
an important focus of research that aims to improve personalized therapies. Unlike current …