Applications of Fusion Techniques in E-Commerce Environments: A Literature Review

Emmanouil Daskalakis, Konstantina Remoundou, Nikolaos Peppes, Theodoros Alexakis, Konstantinos Demestichas, Evgenia Adamopoulou, Efstathios Sykas
2022 Sensors  
The extreme rise of the Internet of Things and the increasing access of people to web applications have led to the expanding use of diverse e-commerce solutions, which was even more obvious during the COVID-19 pandemic. Large amounts of heterogeneous data from multiple sources reside in e-commerce environments and are often characterized by data source inaccuracy and unreliability. In this regard, various fusion techniques can play a crucial role in addressing such challenges and are
more » ... used in numerous e-commerce applications. This paper's goal is to conduct an academic literature review of prominent fusion-based solutions that can assist in tackling the everyday challenges the e-commerce environments face as well as in their needs to make more accurate and better business decisions. For categorizing the solutions, a novel 4-fold categorization approach is introduced including product-related, economy-related, business-related, and consumer-related solutions, followed by relevant subcategorizations, based on the wide variety of challenges faced by e-commerce. Results from the 65 fusion-related solutions included in the paper show a great variety of different fusion applications, focusing on the fusion of already existing models and algorithms as well as the existence of a large number of different machine learning techniques focusing on the same e-commerce-related challenge.
doi:10.3390/s22113998 pmid:35684619 pmcid:PMC9182987 fatcat:63ztbmzfuvdk3hjagtss5iihey