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 ...
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
The subfield of itemset mining is essentially a collection of algorithms. Whenever a new type of constraint is discovered, a specialized algorithm is proposed to handle it. All o...
Daniel Kifer, Johannes Gehrke, Cristian Bucila, Wa...
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
Mining association rules is an important data mining problem. Association rules are usually mined repeatedly in different parts of a database. Current algorithms for mining associa...