Machine Learning in E-Commerce

Maria Enache

Risk in Contemporary Economy, 2020, 111-117

Abstract: In this paper, methods and recommendations for an e-commerce web application of an online e-shop were explored, using various web technologies, such as Python. The approach used is described by analyzing the initial requirements, models and projects of the planned solution and the final implementation of the chosen method using a Model-View-Controller (MVC) framework. To achieve this goal, use case diagrams for specifications and implementation were developed, providing two levels of solutions: basic implementation using cookie functionality and advanced implementation based on the integration of machine learning algorithms. The adequacy and advantages / disadvantages of different methods, such as general recommendation systems and content-based recommendations, were analyzed and presented. This type of implementation is only a first step towards the explicable paradigm of artificial intelligence. Finally, the possibilities for future research are presented, taking into account several applications and other design aspects.

Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.rce.feaa.ugal.ro/images/stories/RCE2020/Enache.pdf (application/pdf)

Related works:
Journal Article: Machine Learning in E-commerce (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ddj:fserec:y:2020:p:111-117

Access Statistics for this article

More articles in Risk in Contemporary Economy from "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Gianina Mihai ().