Building operations account for the largest proportion of energy use throughout the building
life cycle. The energy saving potential is considerable taking into account the existence of a …

In data mining, the classical association rule mining techniques deal with binary attributes;
however, real-world data have a variety of attributes (numerical, categorical, Boolean). To …

Numerical association rule mining is a widely used variant of the association rule mining
technique, and it has been extensively used in discovering patterns and relationships in …

Many algorithms have emerged to address the discovery of quantitative association rules
from datasets in the last years. However, this task is becoming a challenge because the …

Techniques of performance analysis, comprising of various metrics such as accuracy,
efficiency and consuming time, have been conducted to evaluate the measures of properties …

Association rule mining (ARM) techniques are effective in extracting frequent patterns and
hidden associations among data items in various databases. These techniques are widely …

In this study, we propose a fast algorithm to form product-based fuzzy association rules from
large quantitative dataset, which reduces data size and ensures the quality of the obtained …

Fuzzy association rule mining (FARM) is a mainstream method to discover hidden patterns
and association rules in quantitative data. It is essential to improve performance metrics …

In connected health services automatic discovery of recurring patterns and correlations, or
insights, provides many interesting opportunities for the personalization of the services. In …

Fuzzy association rule mining is a popular method to discover hidden patterns and
associations in quantitative data. With fuzzy logic, fuzzy association rule mining is easier for …