Frequent itemset mining: A 25 years review
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 …
A systematic assessment of numerical association rule mining methods
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 …
however, real-world data have a variety of attributes (numerical, categorical, Boolean). To …
A survey of evolutionary computation for association rule mining
Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …
in data mining. It has achieved great success in a plethora of applications such as market …
Combining Apriori heuristic and bio-inspired algorithms for solving the frequent itemsets mining problem
Abstract Exact approaches to Frequent Itemsets Mining (FIM) are characterised by poor
runtime performance when dealing with large database instances. Several FIM bio-inspired …
runtime performance when dealing with large database instances. Several FIM bio-inspired …
Analysis of motorcycle accidents using association rule mining-based framework with parameter optimization and GIS technology
Introduction Analyzing key factors of motorcycle accidents is an effective method to reduce
fatalities and improve road safety. Association Rule Mining (ARM) is an efficient data mining …
fatalities and improve road safety. Association Rule Mining (ARM) is an efficient data mining …
Mining high utility itemsets with hill climbing and simulated annealing
High utility itemset mining (HUIM) is the task of finding all items set, purchased together, that
generate a high profit in a transaction database. In the past, several algorithms have been …
generate a high profit in a transaction database. In the past, several algorithms have been …
Performance analysis of multi-objective artificial intelligence optimization algorithms in numerical association rule mining
Association rules mining (ARM) is one of the most popular tasks of data mining. Although
there are many effective algorithms run on binary or discrete-valued data for the problem of …
there are many effective algorithms run on binary or discrete-valued data for the problem of …
A novel hybrid GA–PSO framework for mining quantitative association rules
Discovering association rules is a useful and common technique for data mining in which
dependencies among datasets are shown. Discovering the rules from continuous numeric …
dependencies among datasets are shown. Discovering the rules from continuous numeric …
A survey on association rules mining using heuristics
Association rule mining (ARM) is a commonly encountred data mining method. There are
many approaches to mining frequent rules and patterns from a database and one among …
many approaches to mining frequent rules and patterns from a database and one among …
CAPHAR: context-aware personalized human activity recognition using associative learning in smart environments
The existing action recognition systems mainly focus on generalized methods to categorize
human actions. However, the generalized systems cannot attain the same level of …
human actions. However, the generalized systems cannot attain the same level of …