Mining Multidimensional Fuzzy Association Rules from a Normalized Database

Intan, Rolly; Yenty, O.

doi:10.1109/ichit.2008.229

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…that involve uncertainties. A number of techniques are reported in the literature [1][2][3][4][5][6][7][8] for data mining. Association rule mining is one of the important types of data mining which has attracted attention of various research workers.…”

Section: Introductionmentioning

confidence: 99%

“…Association rule mining is one of the important types of data mining which has attracted attention of various research workers. A good number of attempts are reported in the literature [1][2][3][4] on development of algorithms for association rule mining in deterministic situations. Apriori algorithm [1,2] is the first algorithm for mining frequent item sets for association rules.…”

Section: Introductionmentioning

confidence: 99%

“…However, based on human intuitive, it should be considered that the larger number of items purchased in a transaction means that the degree of association among the items in the transaction may be lower. This concept was proposed and discussed well in [3,4]. Real world data in the field of engineering, science, technology, medical and social sciences, economics etc.…”

Section: Introductionmentioning

confidence: 99%

“…Although three theories are quite distinct yet deal with vagueness. To deals uncertainty in association rule mining, a number of attempts are reported for development of fuzzy set [4,13,14],rough set [23]and vague set [24] approaches for association rule mining. A wide range of applications of soft sets have been developed in many different fields, including the smoothness of functions, game theory, operations research, Riemann integration, Perron integration, probability theory and measurement theory and its applications.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Absolute Soft Set Approach for Mining Association Patterns

Saraf¹,

Adlakha²,

Sharma³

2013

IJCA

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Absolute Soft Set Approach for Mining Association Patterns

Saraf¹,

Adlakha²,

Sharma³

2013

IJCA

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“…Thus the biological sequence data (Hu et al, 2009) stored at data warehouse in the format of ultidimensional temporal sequential data can be used for finding temporal pattern (Intan and Yenty, 2008). Moreover, due to the highly distributed uncontrolled mining and use of a wide variety of bio medical data, data collection, data analysis and semantic integration of such heterogeneous and widely distributed temporal sequence data has become an important task for systematic and coordinated analysis of medical dataset (Khan et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

A Descriptive Framework for the Multidimensional Medical Data Mining and Representation

Sankaradass¹,

Kannan²

2011

Journal of Computer Science

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Problem statement: Association rule mining with fuzzy logic was explored by research for effective datamining and classification. Approach: It was used to find all the rules existing in the transactional database that satisfy some minimum support and minimum confidence constraints. Results: In this study, we propose new rule mining technique using fuzzy logic for mining medical data in order to understand and better serve the needs of Multidimensional Breast cancer Data applications. Conclusion:The main objective of multidimensional Medical data mining is to provide the end user with more useful and interesting patterns. Therefore, the main contribution of this study is the proposed and implementation of fuzzy temporal association rule mining algorithm to classify and detect breast cancer from the dataset.

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Fuzzy Bayesian Belief Network for Analyzing Medical Track Record

Intan

Yuliana

2010

Advances in Intelligent Information and Database Systems

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Bayesian Belief Network (BBN), one of the data mining classification methods, is used in this research for mining and analyzing medical track record from a relational data table. In this paper, the BBN concept is extended with meaningful fuzzy labels for mining fuzzy association rules. Meaningful fuzzy labels can be defined for each domain data. For example, fuzzy labels secondary disease and complication disease are defined for disease classification. We extend the concept of Mutual Information dealing with fuzzy labels for determining the relation between two fuzzy nodes. The highest fuzzy information gain is used for mining association among nodes. A brief algorithm is introduced to develop the proposed concept. Experimental results of the algorithm show processing time in the relation to the number of records and the number of nodes. The designed application gives a significant contribution to assist decision maker for analyzing and anticipating disease epidemic in a certain area.

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Mining Multidimensional Fuzzy Association Rules from a Normalized Database

Cited by 7 publications

References 5 publications

Absolute Soft Set Approach for Mining Association Patterns

Absolute Soft Set Approach for Mining Association Patterns

A Descriptive Framework for the Multidimensional Medical Data Mining and Representation

Fuzzy Bayesian Belief Network for Analyzing Medical Track Record

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