Qian Wanga,b,c, Jiadong Rena,b, Darryl N Davisc, Yongqiang Chengc
Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 399-404, 2018, DOI:10.1080/10798587.2017.1340135
Abstract Frequent pattern mining usually requires much run time and memory usage. In some applications, only
the patterns with top frequency rank are needed. Because of the limited pattern numbers, quality of
the results is even more important than time and memory consumption. A Frequent Pattern algorithm
for mining Top-rank-K patterns, FP_TopK, is proposed. It is based on a Node-list data structure extracted
from FTPP-tree. Each node is with one or more triple sets, which contain supports, preorder and postorder transversal orders for candidate pattern generation and top-rank-k frequent pattern mining. FP_
TopK uses the minimal support threshold for pruning strategy… More >
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