Study on the Data Mining Algorithm Based on Positive and Negative Association Rules
- Jingrong Yang
- Chunyu Zhao
Abstract
In this article, we systematically, deeply and comprehensively analyzed and studied the association rule data mining technology, and induced, analyzed and researched the typical mining algorithms of association rule and their basic principles, and objectively compare the differences among various algorithms. We used to correlation to measure the relations among item sets, and gave the computations of support level and confidence level of negative association rule based on traditional association rules, and analyzed and researched the operation principle and implementation approaches of this algorithm. Through the demonstration test of the algorithm, the results indicated that the algorithm was effective.
- Full Text: PDF
- DOI:10.5539/cis.v2n2p103
Journal Metrics
WJCI (2022): 0.636
Impact Factor 2022 (by WJCI): 0.419
h-index (January 2024): 43
i10-index (January 2024): 193
h5-index (January 2024): N/A
h5-median(January 2024): N/A
( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )
Index
- Academic Journals Database
- BASE (Bielefeld Academic Search Engine)
- CiteFactor
- CNKI Scholar
- COPAC
- CrossRef
- DBLP (2008-2019)
- EBSCOhost
- EuroPub Database
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- Google Scholar
- Harvard Library
- Infotrieve
- LOCKSS
- Mendeley
- PKP Open Archives Harvester
- Publons
- ResearchGate
- Scilit
- SHERPA/RoMEO
- Standard Periodical Directory
- The Index of Information Systems Journals
- The Keepers Registry
- UCR Library
- Universe Digital Library
- WJCI Report
- WorldCat
Contact
- Chris LeeEditorial Assistant
- [email protected]