Mining frequent patterns has been a topic of active research because it is computationally the most expensive step in association rule discovery. In this paper, we discuss the use ...
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...
Abstract. Consumer research has indicated that consumers use compensatory and non-compensatory decision strategies when formulating their purchasing decisions. Compensatory decisio...
Timothy Maciag, Daryl H. Hepting, Dominik Slezak, ...
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
The Euclidean distance transform of a binary image is the function that assigns to every pixel the Euclidean distance to the background. The Euclidean feature transform is the fun...