A well-known problem that limits the practical usage of association rule mining algorithms is the extremely large number of rules generated. Such a large number of rules makes the...
Girish Keshav Palshikar, Mandar S. Kale, Manoj M. ...
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
A rule set generation technique based on a generated decision tree is suggested for better decision making to compensate the weak point of decision trees
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
The mining of weighted association rules is one of the primary methods used in communication alarm correlation analysis. With large communication alarm database, the traditional me...
This paper presents new textural features which are based on association rules. We give a texture representation, which is an appropriate formalism, that allows straightforward app...
Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
In order to allow for the analysis of data sets including numerical attributes, several generalizations of association rule mining based on fuzzy sets have been proposed in the li...
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for ...
The main focus of image mining in the proposed method is concerned with the classification of brain tumor in the CT scan brain images. The major steps involved in the system are: p...