Absolute Soft Set Approach for Mining Association Patterns

Abstract

Molodtsov initiated the concept of soft set as a new mathematical tool for dealing with uncertainties. In 2003, Maji put forward several notions on Soft Set Theory. In this paper, absolute soft set approach has been developed for mining association patterns from a transactional data set. This approach is used for mining associations has been illustrated with the help of an example and experiment on a real world data set. In particular, the work demonstrates that absolute soft set theory can be applied to problems that contain uncertainties especially in decision making problems. The proposed approach gives better picture of association relationship, confidence levels and is helpful in addressing the absolute association patterns.

Enhancing Customer Relationship Management Using Fuzzy Association Rules and the Evolutionary Genetic Algorithm

“…No element in 𝑌𝑌 is the source of any element in X; This is Y ∩C estors (x) = φ because the pattern rule "x⇒ ancestors (x) = φ " is fairly true with 100% confidence, and is redundant. X and Y may each contain Γ elements of any level of Γ [12][13] [14].…”

“…A more formal description, as well as a survey of the existing methods of quantitative association rule mining, can be found in [17]. www.ijacsa.thesai.org Numerous scholars have absorbed fuzzy multilevel association rules mining in the literature [13][14][15][16][17]. Without specifying the actual minimum support, certain of these solutions suggested multilayer membership functions via systems of ant colonies and genetic algorithms.…”

“…By utilizing the genetic algorithm's capacity to swiftly identify without completing exhaustive searches, numerous solutions can be found simultaneously in a huge multidimensional problem. our proposed technique can improve mining efficiency while maintaining the desired precision but avoiding the exhaustive list of potential association rules The definitions listed below are those connected to multilevel association rules [12][13] [14]:…”

A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

“…By using the advantage of the genetic algorithm, which can efficiently ascertain multiple solutions concurrently in a large multidimensional problem without conducting exhaustive searches, our offered method can enhance the mining performance while preserving the wanted accuracy but bypassing the exhausting list of association rule candidates. Definitions linked to multilevel association rules are presented as follows [9][15] [16]:…”