We study the inference on the interesting association rules. Then we define the concept of the representative basis for interesting association rules extracted from a dataset D, a...
We study KDD (Knowledge Discovery in Databases) processes on OLAP (multidimensional and multilevel) data from a query point of view. Focusing on association rule mining, we consid...
Association rules discovery is one of the most important tasks in Knowledge Discovery in Data Bases. Since the initial APRIORI algorithm, many efforts have been done in order to de...
Association rule mining techniques are used to search attribute-value pairs that occur frequently together in a data set. Ordinal association rules are a particular type of associa...
Alina Campan, Gabriela Serban, Traian Marius Truta...
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
The problem of the relevance and the usefulness of extracted association rules is becoming of primary importance, since an overwhelming number of association rules may be derived f...
Ghada Gasmi, Sadok Ben Yahia, Engelbert Mephu Ngui...
Traditional framework for mining association rules has pointed out the derivation of many redundant rules. In order to be reliable in a decision making process, such discovered rul...
The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing. Material and Methods: Association rules method is...
Data mining has emerged to address the problem of transforming data into useful knowledge. Although most data mining techniques, such as Association Rules, substantially reduce th...
Generalized association rules are rules that contain some background knowledge, therefore, giving a more general view of the domain. This knowledge is codified by a taxonomy set ...
Veronica Oliveira de Carvalho, Solange Oliveira Re...