Examining the Correlation Between Big Data Analytics for Online-to-Offline Market Models: A Research Review

The exponential growth of software has made it possible for consumers to bypass traditional brick-and-mortar stores in favor of online ones. The newest e-commerce layout targeted to professional and academic interests is cross-platform. Due to the network's foundation of online-to-offline providers, as well as customers' limited availability of product-related data, optimization is challenging. The authors analyzed the idea of similarity and then presented a novel approach for evaluating massive data sets called the BDA-O2O-MM. The cooperative similarity, the choice similarity, and the direction similarity are employed as indications of similarity in this method. Multiple similarity factors are superior to one for predicting achievement in various settings. Pros debate whether the aggregate or individual similarities between paths are more interesting. The proposed BDA-O2O-MM model enhances the precision ratio of 94%, recall ratio of 92
^%
, accuracy ratio of 97%, delay rate of 41%, and F score rate of 95% compared to other existing systems.