In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
A major challenge in frequent-pattern mining is the sheer size of its mining results. To compress the frequent patterns, we propose to cluster frequent patterns with a tightness m...
Local pattern mining algorithms generate sets of patterns, which are typically not directly useful and have to be further processed before actual application or interpretation. Ra...
Most algorithms for mining interesting spatial colocations integrate the co-location / clique generation task with the interesting pattern mining task, and are usually based on th...
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...