Abstract
One of problems in frequent pattern (FP) mining is how to reduce the number of patterns in collection which usually are in huge numbers. To solve the problem, two classes of approximate frequent pattern i.e. closed frequent pattern and maximal frequent pattern have been proposed. In fact, the number of closed frequent pattern is still very huge and leads to ineffectiveness and inefficiency when exploring the patterns. In contrast, the number of maximal frequent term set (MFT) in collection is usually smaller than closed frequent itermset(CFT). MFT is able to represent long or specific term sets in dataset and useful in some data mining area. Our previous work has introduced a novel notion about frequent contextual term set (FCT). The number of FCT's pattern in collection is much smaller than CFT's and this is an advantage of using FCT. In this paper we present our further investigation about FCT compared to CFT and MFT. The investigation is aimed to figure out the position of FCT amongst those two classes of frequent term set. Experimental work and mathematical approach are developed for this investigation. It is shown that FCT is closed frequent term set and contains MFT.
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