Finding Fuzzy Close Frequent Itemsets from Databases
Haifeng Li, Yuejin Zhang, Mo Hai, Hanqing Hu · Procedia Computer Science · 2018
In this paper, we define the problem of fuzzy close frequent itemset mining to discover the rules of the data. A concise tree-based data synoposis named FCTree is built, where the fuzzy itemsets are sorted by their supports. In addition, an algorithm called FCFIMiner is proposed to construct and maintain the FCTree. We conduct superset pruning from the result of the FCTree. The experimental works over 2 databases show the proposed algorithm has a much better performance.