Survey of Automated Recommender System for Web Applications

Authors

  • Vinutha KN Department of Computer Science, VTU, Karnataka, India
  • KS Sampada Department of Computer Science, VTU, Karnataka, India

Keywords:

Feature Vector, Recommender System, Cross-Browser Compatibility, Web Crawling Technique

Abstract

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.

References

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S. R. Choudhary, M. R. Prasad, and A. Orso, “X-pert: accurate identification of cross-browser issues in web applications,” in ICSE, 2013, pp. 702–711. [6] BMWI, “Exist,” www.exist.de.

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Published

2025-11-11

How to Cite

[1]
K. Vinutha and K. Sampada, “Survey of Automated Recommender System for Web Applications”, Int. J. Comp. Sci. Eng., vol. 4, no. 3, pp. 36–39, Nov. 2025.

Issue

Vol. 4 No. 3 (2016): IJCSE Special Issue May Edition

Section

Review Article

License

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