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An Algorithm to Mine Normalized Weighted Sequential Patterns Using a Prefix-projected Database

Demetrovics, JanosThi, Vu DucDuong, Tran Huy — 2015

Serdica Journal of Computing

Sequential pattern mining is an important subject in data mining with broad applications in many different areas. However, previous sequential mining algorithms mostly aimed to calculate the number of occurrences (the support) without regard to the degree of importance of different data items. In this paper, we propose to explore the search space of subsequences with normalized weights. We are not only interested in the number of occurrences of the sequences (supports of sequences), but also concerned about...

A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance

Thien, Nguyen VanDemetrovics, JanosThi, Vu DucGiang, Nguyen LongSon, Nguyen Nhu — 2016

Serdica Journal of Computing

In fuzzy granular computing, a fuzzy granular structure is the collection of fuzzy information granules and fuzzy information granularity is used to measure the granulation degree of a fuzzy granular structure. In general, the fuzzy information granularity characterizes discernibility ability among fuzzy information granules in a fuzzy granular structure. In recent years, researchers have proposed some concepts of fuzzy information granularity based on partial order relations. However, the existing...

On the Time Complexity of the Problem Related to Reducts of Consistent Decision Tables

Janos, DemetrovicsThi, Vu DucGiang, Nguyen LongDuong, Tran Huy — 2015

Serdica Journal of Computing

In recent years, rough set approach computing issues concerning reducts of decision tables have attracted the attention of many researchers. In this paper, we present the time complexity of an algorithm computing reducts of decision tables by relational database approach. Let DS = (U, C ∪ {d}) be a consistent decision table, we say that A ⊆ C is a relative reduct of DS if A contains a reduct of DS. Let s = <C ∪ {d} , F> be a relation schema on the attribute set C ∪ {d}, we say that A ⊆ C...

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