Classification is one of the key issues in the fields of decision sciences and knowledge discovery. This paper presents a new approach for constructing a classifier, based on an e...
Guoqing Chen, Hongyan Liu, Lan Yu, Qiang Wei, Xing...
Abstract Computing frequent itemsets is one of the most prominent problems in data mining. Recently, a new related problem, called FREQSAT, was introduced and studied: given some i...
We discovered that the set of frequent hybrid sequential patterns obtained by previous researches is incomplete, due to the inapplicability of the Apriori principle. We design and ...
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...
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...