2012 ©
             Publication
Journal Publication
Title of Article Association Mining Rule Applied to Optimal Shopping Path and Layout: A Case Study of Supermarket in Thailand 
Date of Acceptance 25 June 2020 
Journal
     Title of Journal International Journal of Advanced Science and Technology 
     Standard SCOPUS 
     Institute of Journal Science and Engineering Research Support Society  
     ISBN/ISSN 2005-4238 
     Volume  
     Issue  
     Month
     Year of Publication 2020 
     Page  
     Abstract The association rule was a data mining techniques, which was important in knowledge discovery association of data. Finding the association between each shelf could benefit both customers and business how to place layout in supermarket. This work was focused on exploring the association rules analysis applied to each shelve of products by comparing two techniques of association rules as the FP-Growth algorithm and Apriori. According to this study, it was found that the application of FP-Growth algorithm was more suitable method for exploring the association rules of the shelves in the shop than Apriori. In addition, the results of the study revealed that the FP-Growth algorithm processed more quickly than Apriori as considered the running time to analysis layout of supermarket. The Apriori took average of time as 656.43 seconds and FP-Growth algorithm took average of time as 82.93 seconds that average of reduced time to 87.37%. Moreover, this study proposed an analysis of the efficiency improvement in disposing the shelves for the benefit of increasing business income through improving the shelves layout based on the association rules obtained from shopping path results of the study. 
     Keyword Association Rule, Data Mining, FP-Growth Algorithm, Apriori 
Author
597020063-7 Mr. JAKKRIT KAEWYOTHA [Main Author]
College of Computing Doctoral Degree

Reviewing Status มีผู้ประเมินอิสระ 
Status ได้รับการตอบรับให้ตีพิมพ์ 
Level of Publication นานาชาติ 
citation false 
Part of thesis true 
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