Li, Yingshan (2024) Research on Association Mining Method of Frequent Itemsets in High-dimensional Multi-source Big Data. In: Proceedings of the 3rd International Conference on Public Management and Big Data Analysis, PMBDA 2023, December 15–17, 2023, Nanjing, China.
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Abstract
The conventional association mining method of frequent itemsets in high-dimensional multi-source big data mainly uses the framework of Parameter Server to solve the problem, which is easily influenced by the change of data attribute relationship, resulting in low accuracy of data association mining.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 17:33 |
| Last Modified: | 16 Apr 2026 23:46 |
| URI: | http://eprints.eai.eu/id/eprint/48851 |
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