In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Sequential Data This paper is about the unsuperviseddiscovery of patterns in sequencesof compositeobjects. A compositeobject may be describedas a sequenceof other, simpler data. In...
Learning management systems capture student's interactions with the course contents in the form of event logs, including the order in which resources are accessed. We build on...
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...