Survey of Automated Recommender System for Web Applications - Vinutha, KN; Sampada, KS (International Journal of Computer Sciences and Engineering, 2025)
Online shopping new way of business in present days based on the previous surfing and purchasing products are recommended to the users. The existing method of recommending the product has to undergo several processes or functionalities and these processes or functionalities are manually tested for the accuracy. The manual testing method requires lot of time and money and other resources. To overcome the problem this paper proposes a Automation Testing for the recommender system, with Feature Vector Algorithm and perform a automation on each modules of the Feature Vector algorithm and also checks the Cross-Browser compatibility across the browser and also collecting the online reviews from by using Web Crawling Technique.