Apriori and neural network algorithm for university databases and financial application using data mining algorithms - Muniyan, Krishnamoorthy; Ramakrishnan, Karthikeyan (AIP conference proceedings, 2023)
Currently, with the spread of networks, all kinds of management-related data information is exploding, and with the development of society, a large amount of storage resource management of universities with many kinds of resources and storage is accumulated increase. With the rapid increase in the amount of data and the nature of media data resources, and the growing demand for user network access to data resources, this requires optimization of university databases, making it more appropriate for university users. Browse to and read data resources. In light of the present circumstance, this paper concentrated on the deduced affiliation rule mining calculation in the college the board framework. Since the college’s advanced information document was the premise of calculation streamlining research, we initially took a gander at the college’s computerized information file and afterward took a gander at the pre-calculations exhaustively, and this article gave a few outcomes. At long last, we analyzed exhaustively the use of deduced affiliation rule mining calculations in college the board frameworks. Test results show that the utilization of deduced affiliation rule mining calculations in college the executive’s frameworks has wide points of view and that objective use can be of extraordinary worth. The evaluations in this white paper are reliable, efficient retrieval of data and the evaluation results provide a useful reference for applying pre-algorithms for association rule mining. The rules of the Apriori Mining Association pointed to further research and the application of algorithms in the management of universities databases of the system.