DEVELOPMENT OF RECOMMENDATION FUNCTIONS FOR FOOD SUPERMARKET E-COMMERCE SYSTEMS

Mariia Seleznova; Andrii Kovalenko

doi:10.36074/logos-15.11.2024.037

Information technologies and systems

November 15, 2024; Bologna, Italy: VI International Scientific and Practical Conference «RICERCHE SCIENTIFICHE E METODI DELLA LORO REALIZZAZIONE: ESPERIENZA MONDIALE E REALTÀ DOMESTICHE»

DEVELOPMENT OF RECOMMENDATION FUNCTIONS FOR FOOD SUPERMARKET E-COMMERCE SYSTEMS

Mariia Seleznova ⁺⁻
Andrii Kovalenko ⁺⁻

DOI: https://doi.org/10.36074/logos-15.11.2024.037
Published: 02.12.2024

Abstract

Introduction. Currently, recommendation systems have become widely used to increase sales volumes, providing customers with the convenience of choosing products or services based on their personal preferences. The task of implementing recommendation functions in e-commerce systems is to determine methods for obtaining and analyzing customer preference data. With the help of these methods, the system automatically generates various types of recommendations for customers, suggesting product purchases.

References

Jannach, D., Zanker, M., Felfernig, A., & Friedrich, G. (2010). Recommender Systems: An Introduction. New York: Cambridge University Press. https://doi.org/10.1017/CBO9780511763113.
Charu, C. (2016). Recommender Systems: The Textbook. Springer, Switzerland. https://doi.org/10.1007/978-3-319-29659-3.
Madavi, P., Tekam, J., & Khirekar, D. (2024). Movie Recommendation System. International Journal of Advanced Research in Science, Communication and Technology (IJARSCT). Vol. 4, pp. 320-324. https://doi.org/10.48175/IJARSCT-17453 320.
Paul, D., & Kundu, S. (2020). A Survey of Music Recommendation Systems with a Proposed Music Recommendation System. Advances in Intelligent Systems and Computing. Vol 937, 279–285. https://doi.org/10.1007/978-981-13-7403-6_26.
Devika, P. & Milton, A. (2024). Book recommendation system: reviewing different techniques and approaches. Int J Digit Libr. Vol. 25, 803–824. https://doi.org/10.1007/s00799-024-00403-7.
Margaret H Dunham, Yongqiao Xiao, Le Gruenwald, & Zahid Hossain. (2000). A survey of association rules. Southern Methodist University. https://www.researchgate.net/publication/240737786.

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How to Cite

Seleznova , M., & Kovalenko , A. (2024). DEVELOPMENT OF RECOMMENDATION FUNCTIONS FOR FOOD SUPERMARKET E-COMMERCE SYSTEMS. Collection of Scientific Papers «ΛΌГOΣ», (November 15, 2024; Bologna, Italy), 152–159. https://doi.org/10.36074/logos-15.11.2024.037

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[1] Jannach, D., Zanker, M., Felfernig, A., & Friedrich, G. (2010). Recommender Systems: An Introduction. New York: Cambridge University Press. https://doi.org/10.1017/CBO9780511763113.

[2] Charu, C. (2016). Recommender Systems: The Textbook. Springer, Switzerland. https://doi.org/10.1007/978-3-319-29659-3.

[3] Madavi, P., Tekam, J., & Khirekar, D. (2024). Movie Recommendation System. International Journal of Advanced Research in Science, Communication and Technology (IJARSCT). Vol. 4, pp. 320-324. https://doi.org/10.48175/IJARSCT-17453 320.

[4] Paul, D., & Kundu, S. (2020). A Survey of Music Recommendation Systems with a Proposed Music Recommendation System. Advances in Intelligent Systems and Computing. Vol 937, 279–285. https://doi.org/10.1007/978-981-13-7403-6_26.

[5] Devika, P. & Milton, A. (2024). Book recommendation system: reviewing different techniques and approaches. Int J Digit Libr. Vol. 25, 803–824. https://doi.org/10.1007/s00799-024-00403-7.

[6] Margaret H Dunham, Yongqiao Xiao, Le Gruenwald, & Zahid Hossain. (2000). A survey of association rules. Southern Methodist University. https://www.researchgate.net/publication/240737786.