Tools
Tools
Pandey, Shivam (2022) Enhancement of Apriori Algorithm for Applications of Data Mining using Frequent Pattern Tree. Masters thesis, Dublin, National College of Ireland.
Preview |
PDF (Master of Science)
Download (1MB) | Preview |
Preview |
PDF (Configuration manual)
Download (1MB) | Preview |
Abstract
This research work shed light on the topic of enhancement of the Apriori algorithm in the application of Data Mining using cloud database platform. In this study, a clear description about the Apriori algorithm is stated and an example based on grocery database is taken to execute the Apriori algorithm for generating the frequent item sets. Finally a comparison among Apriori algorithm and FP growth algorithm has been done on the discussion section. During the implementation we have used cloud services from AWS like EC2 which helps to create instance which is easy to mange and configure. To sore the large amount of data S3 service of AWS is used which allows data to store and retrieve from anywhere. As our main aim to reduce to time complexity or time of execution of the dataset from cloud. EMR service of AWS has been utilized which internally uses Map-Reduce which help to process the large amount of data in a very less time which saves and execution cost of the large databases. In our research we have used 4 different size of database of 1000, 4000, 15000, 25000 records
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Apriori algorithm; improved apriori algorithm; itemsets; frequent itemset; candidate itemset; time and space complexity; Big Data; cloud computing; MapReduce |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing |
| Divisions: | School of Computing > Master of Science in Cloud Computing |
| Depositing User: | Tamara Malone |
| Date Deposited: | 29 Nov 2022 17:37 |
| Last Modified: | 06 Dec 2022 18:08 |
| URI: | https://norma.ncirl.ie/id/eprint/5944 |
Actions (login required)
 |
View Item |