High-utility itemset mining has evolved as an essential and captivating research topic. It
aims to extract the patterns/itemsets having high utility value; hence, they are called high …

Privacy protection has become a predominant concern in big data analysis. Privacy-
Preserving Association Rule Mining (PPARM) is a process in which original data is …

This paper introduces a new theoretical scheme for the solution of the frequent itemset
hiding problem. We propose an algorithmic approach that consists of a novel constraint …

Interrupting, altering, or stealing autism-related sensitive data by cyber attackers is a
lucrative business which is increasing in prevalence on a daily basis. Enhancing the security …

Privacy preservation is increasingly crucial in e-Health systems, particularly within the realm
of privacy-preserving data mining, which aims to reveal underlying patterns while …

Mientras que las bioseñales EEG proveen un nivel de entendimiento respecto a la actividad
cerebral, métodos computacionales de Ingeniería de Software e Inteligencia Artificial …

This paper introduces a spark-based fast solution for privacy-preserving frequent pattern
mining problems for big data. Spark Resilient Distributed Dataset (RDD) framework has …

Sharing a transaction database with other parties for exploring valuable information
becomes more recognized by business institutions, ie, retails and supermarkets. It offers …

Humanistic courses are a requirement of the Autonomous University of Aguascalientes for
all its students, who must take at least three courses from different disciplines during their …

Interrupting, altering, or stealing autism-related sensitive data by cyber attackers is a
lucrative business which is increasing in prevalence on a daily basis. Enhancing the security …