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 …

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 …

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 …

This book is intended to provide a general and comprehensible overview of the field of
pattern mining with evolutionary algorithms. To do so, the book provides formal definitions …

Pattern mining is one of the most important tasks to extract meaningful and useful
information from raw data. This task aims to extract item-sets that represent any type of …

Traditional association rule mining based on the support–confidence framework provides
the objective measure of the rules that are of interest to users. However, it does not reflect …

Mobile recommender systems target on recommending the right product or information to
the right mobile users at anytime and anywhere. It is well known that the contextual …

Teacher evaluation is presented as an object of study of great interest, where multiple efforts
converge to establish models from the association of heterogeneous data from academic …

This paper proposes the application of association rule mining to improve quizzes and
courses. First, the paper shows how to preprocess quiz data and how to create several data …

Association rule mining is one of the most important tasks to describe raw data. Although
many efficient algorithms have been developed to this aim, existing algorithms do not work …