Association Rules Analysis Using Algorithm Apriori And Fuzzy Normalization

2021 ◽  
Author(s):  
Meri Nova Marito Br.Sipahutar ◽  
Opim Salim Sitompul ◽  
Sutarman
Keyword(s):  
Association Rules ◽  
Association Rules Analysis

scholarly journals Correction: Lee et al. Patterns of Multimorbidity in Adults: An Association Rules Analysis Using the Korea Health Panel. Int. J. Environ. Res. Public Health 2020, 17, 2618

2021 ◽  
Vol 18 (21) ◽  
pp. 11278
Author(s):  
Yoonju Lee ◽  
Heejin Kim ◽  
Hyesun Jeong ◽  
Yunhwan Noh
Keyword(s):  
Public Health ◽  
Association Rules ◽  
Association Rules Analysis

The authors have noticed an inadvertent error in our article, ‘‘Patterns of Multimorbidity in Adults: An Association Rules Analysis Using the Korea Health Panel” [...]

scholarly journals A Novel Intelligence Recommendation Model for Insurance Products with Consumer Segmentation

2014 ◽  
Vol 2 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Wei Xu ◽  
Jiajia Wang ◽  
Ziqi Zhao ◽  
Caihong Sun ◽  
Jian Ma
Keyword(s):  
Association Rules ◽  
Insurance Industry ◽  
Insurance Company ◽  
Growth Opportunities ◽  
Consumer Group ◽  
Transaction Data ◽  
Consumer Segmentation ◽  
Cost Of Time ◽  
Effective Product ◽  
Association Rules Analysis

AbstractAs one of the financial industries, the insurance industry is now facing a vast market and significant growth opportunities. The insurance company will generate a lot transaction data each day, thus forming a huge database. Recommending insurance products for customers accurately and efficiently can help to improve the competitiveness of insurance company. Data mining technologies such as association rules have been applied to the recommendation of insurance products. However, large policyholders’ data will be calculated when it being processed with associate rule algorithm. It not only requires higher cost of time and space, but also can lead to the final rules lack of accuracy and differentiation. In this paper, a recommendation model for insurance products based on consumer segmentation is constructed, which first divides consumer group into different classes and then processed with associate rule algorithm. The empirical results show that our proposed method not only makes the consumption of association rules analysis reduced, it has also got more effective product recommendation results.

scholarly journals Association Rules Analysis of Comorbidity and Multimorbidity: The Concord Health and Aging in Men Project

2015 ◽  
Vol 71 (5) ◽  
pp. 625-631 ◽  
Author(s):  
Fabian P. Held ◽  
Fiona Blyth ◽  
Danijela Gnjidic ◽  
Vasant Hirani ◽  
Vasikaran Naganathan ◽  
...  
Keyword(s):  
Association Rules ◽  
Association Rules Analysis

scholarly journals Association Rules Analysis on FP-Growth Method in Predicting Sales

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan ◽  
Mesran Mesran ◽  
Andre Hasudungan Lubis ◽  
Ali Ikhwan ◽  
Supiyandi
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Frequent Itemset ◽  
Frequent Pattern ◽  
Data Set ◽  
Pattern Processing ◽  
Large Databases ◽  
Growth Method ◽  
Association Rules Analysis ◽  
A Company

Sales transaction data on a company will continue to increase day by day. Large amounts of data can be problematic for a company if it is not managed properly. Data mining is a field of science that unifies techniques from machine learning, pattern processing, statistics, databases, and visualization to handle the problem of retrieving information from large databases. The relationship sought in data mining can be a relationship between two or more in one dimension. The algorithm included in association rules in data mining is the Frequent Pattern Growth (FP-Growth) algorithm is one of the alternatives that can be used to determine the most frequent itemset in a data set.

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