Abstract The authors propose an efficient algorithm, NB-MAFIA, for mining maximal frequent itemset using NList, which uses node list of prefix tree to represent itemsets. By using N-List, itemsets’ support can be efficiently computed because of the high compactness of N-List and the efficiency of the method to intersect two N-Lists. Meanwhile, the authors employ some search space pruning strategies and superset checking strategy to improve NB-MAFIA. To evaluate NB-MAFIA, the authors compare proposed algorithm with two state-of-the-art algorithms on a variety of real and synthesis datasets. Experimental results show that NB-MAFIA is efficient and outperform the baseline algorithms in most case. Especially, NB-MAFIA is more efficient on dense datasets.

Ontology is defined as an explicit formal specification of a shared conceptualization. It can provide semantic meaning through relations between concepts. As a fine model for presenting hierarchy and semantic meaning of concepts, Ontology is widely concerned and extensively applied to many fields in computer science and technology. With regard to little research on ontology in China, The state of the art of ontology is surveyed in this paper. This work first analyzes connotation and methodology of ontology, and then analyzes its applications in information system in details. The paper ends with a short conclusion and future work.