We present AIM2-F, an improved implementation of AIM-F [4] algorithm for mining frequent itemsets. Past studies have proposed various algorithms and techniques for improving the e...
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Templat...
Mohammed Javeed Zaki, Nilanjana De, Feng Gao, Paol...
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
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...
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...