ShopSculpt : Crafting Your Cart with Intelligent Ingenuity

Authors

  • Karishma Phapale  Computer Engineering, Savitribai Phule Pune University, Pune, Maharashtra, India
  • Chetan Rathod  Computer Engineering, Savitribai Phule Pune University, Pune, Maharashtra, India
  • Vaibhav Vhankade  Computer Engineering, Savitribai Phule Pune University, Pune, Maharashtra, India

DOI:

https://doi.org/10.32628/CSEIT2410123

Keywords:

Apriori Algorithm, Chi-Square Test, Association Rule.

Abstract

In the present world from small companies to giant company’s product recommendation system plays a very major role, also people are very much interested in online shopping these days, so Recommendations are utilized to make the customer's job easier and faster. The majority of these recommendations are made based on their previous transaction history and association rules generated from it. Apriori Algorithm is the most widely used method for generating association rules based on frequent product sets. But it has a drawback, while generating association rules it uses the whole transactions list and frequent product sets, ignoring the seasonal transactions for generating rules. Hence seasonal transactions are not considered for mining rules, if a person is buying a cake for Christmas, it’s very likely that recommender system recommends birthday balloons, birthday caps as recommendations. But actually, it should recommend Christmas related products for recommendation. To solve this problem, we proposed a model using chi square test with improvised Apriori algorithm. This research paper introduces ShopSculpt, an innovative automated shopping cart system designed to enhance the user shopping experience by leveraging intelligent algorithms. ShopSculpt employs a multifaceted approach, considering user shopping interests, patterns, seasonal trends, and current weather conditions to provide personalized and context-aware product recommendations. The aim is to create a dynamic and responsive shopping environment that adapts to individual preferences and external factors, thereby optimizing the user's shopping journey.

References

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Published

2024-02-29

Issue

Section

Research Articles

How to Cite

[1]
Karishma Phapale, Chetan Rathod, Vaibhav Vhankade, " ShopSculpt : Crafting Your Cart with Intelligent Ingenuity" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 10, Issue 1, pp.150-153, January-February-2024. Available at doi : https://doi.org/10.32628/CSEIT2410123