Modeling the Computational Solution of Market Basket Associative Rule Mining Approaches Using Deep Neural Network

摘要

Data is an important property to everyone and lots of it is generated daily. The large amount of data available in the world today, is stored in repositories, databanks, data warehouses etc. Generated data is further on the rise with the Internet, resulting in the consequent explosion of data and its usage. Data convergence over the Internet, has made it more imperative to analyze data relations due to the tremendous sizes that scales up to petabytes of data. But, there exists inherent challenges of extracting useful data from these large repositories. Thus, focal point of this study is to model a rule-based computational solution to the inherent challenge. We thus propose the use of a market basket dataset mining using a hybrid deep learning associative rule mining heuristic.