Usage Data for Predicting User Trends and Behavioral Analysis in E-Commerce Applications

Autor:	Sridhar Udayakumar, A K Ilavarasi, V Saravanan, V Sathiyamoorthi, T. Nadana Ravishankar, N Jayapandian, Karthikeyan Harimoorthy
Rok vydání:	2021
Předmět:	Behavioral analysis Information Systems and Management business.industry Computer science Strategy and Management E-commerce Management Science and Operations Research business Data science Usage data Information Systems Management Information Systems
Zdroj:	International Journal of Information Systems in the Service Sector. 13:40-61
ISSN:	1935-5696 1935-5688
Popis:	Reviewing and buying the right goods from online websites is growing day by day in today's fast internet environment. Numerous goods in the same label are available to consumers. It is thus a difficult job for consumers to pick up the correct commodity at a decent price under different market conditions. Therefore, it is important for owners of online shopping websites to better understand their customers' needs and offer better services. For these reasons, the access log documented a vast amount of data related to user interactions with the websites. This access log therefore plays a key role in predicting user access trends and in recommending the best product to consumers. This research work therefore focuses on one such methodology for evaluating the pattern and behavioral analysis of users in e-commerce websites.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::17065c098c6997f968f4f896aa9efac3 https://doi.org/10.4018/ijisss.2021100103 Zobrazit plný text záznamu