Stable periodic-frequent itemset mining is essential in big data analytics with many real-
world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a …

Nowadays, the concept of data mining is employed widely and created a great deal of
attention due to its fast arrival. Numerous approaches to frequent itemsets and association …

The personalized recommendation method of higher education resources currently cannot
carry out multidimensional association analysis of learners, situations, and resources and …

The results of gender equality indicators across the world in the form of prevalence of
intimate partner violence (IPV) against women are striking and has thus drawn the attention …

With the rapid growth of data scale and diversification of demand, people have an urgent
desire to extract useful frequent itemset from datasets of different scales. It is no doubt that …

Big data refers to the large amount of information that is collected from different areas and
shared on the internet. However, this development has led to difficulties in using frequent …

A considerable fraction of the female workforce worldwide is making ends meet by doing
various jobs informally at home or in nearby places, rather than at employers' premises. The …

In big data, the frequent item set mining is an important framework for many applications.
Several techniques were used to mine the frequent item sets, but for the collapsed and …

Traditional investment analysis algorithms usually only analyze the similarity between
financial time series and financial data, which leads to inaccurate and inefficient analysis of …

A considerable fraction of the female workforce worldwide is making ends meet by doing
various jobs informally at home or in nearby places, rather than at employers' premises. The …