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2015
DOI: 10.14569/ijacsa.2015.060625
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Vague Set Theory for Profit Pattern and Decision Making in Uncertain Data

Abstract: Abstract-Problem of decision making, especially in financial issues is a crucial task in every business. Profit Pattern mining hit the target but this job is found very difficult when it is depends on the imprecise and vague environment, which is frequent in recent years. The concept of vague association rule is novel way to address this difficulty. Merely few researches have been carried out in association rule mining using vague set theory. The general approaches to association rule mining focus on inducting… Show more

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Cited by 10 publications
(5 citation statements)
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References 17 publications
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“…e work conducted by Pandey et al [23] mentions the computing mechanism for mining vague association rules (VARs) for class course information from the temporal database. Another dimension has been explored by Badhe et al [6] in the form of new model for mining profitable patterns from the transactional dataset. In the sequence, the work mentioned in [24,25] has presented genetic-based methodology for mining hesitated itemsets in the transactional dataset.…”
Section: Hesitationmentioning
confidence: 99%
See 1 more Smart Citation
“…e work conducted by Pandey et al [23] mentions the computing mechanism for mining vague association rules (VARs) for class course information from the temporal database. Another dimension has been explored by Badhe et al [6] in the form of new model for mining profitable patterns from the transactional dataset. In the sequence, the work mentioned in [24,25] has presented genetic-based methodology for mining hesitated itemsets in the transactional dataset.…”
Section: Hesitationmentioning
confidence: 99%
“…e objective of analysis is to know the buying patterns of customers on the basis of their liking and disliking. As evident from the literature, the analytics act has been exercised to reveal various types of patterns such as Frequent Patterns [1][2][3][4][5], Profitable Patterns [6], Conditional Patterns [7], Calendar-Based Patterns [8], and Log Pattern Mining [9] using various techniques of pattern mining [10]. Moreover, after the success of mining knowledge from datasets, researchers deal with certain specific situations and perform various tasks such as mining on data streams [11,12], recognition of handwritten expression [13], investigating customer buying behavior through Visual Market Basket Analysis (VMBA) [14], automated assessment of shopping behavior [15,16], applying additional interestingness measures for association rule mining [17], and conditional discriminative pattern mining [18], and researchers also have to deal to improve the implementation of pattern mining algorithms using time stamp uncertainties and temporal constraints [19], privacy of frequent itemset mining using randomized response [20], and finding infrequent itemset to discover the negative association rule [21].…”
Section: Introductionmentioning
confidence: 99%
“…If an animal index is i, then its nearest neighbor has index of i − 2,i − 1,i,i + 1,i + 2. Once the topology of nearest neighbor is built, the nearest is determined as follows (Badhe et al, 2015):…”
Section: Animal Migration Optimizationmentioning
confidence: 99%
“…Vivek Badhe et al [21] proposed a model for profit pattern mining. They have demonstrated the difficulty in making decisions, particularly in financial problems which is a critical job in industry.…”
Section: Literature Reviewmentioning
confidence: 99%