A Hybrid Approach for Performing Accurate prediction of Green Products using Recommender System

Authors

  • Kaur J Computer Science and Engineering, I.K Gujral Punjab Technical University, Jalandhar, India
  • Bedi RK Computer Science and Engineering, Beant College Of Engineering and Technology, Gurdaspur, India
  • Gupta SK Computer Science and Engineering, Beant College Of Engineering and Technology, Gurdaspur, India

DOI:

https://doi.org/10.26438/ijcse/v6i10.136139

Keywords:

Configuration, Recommender system, KNN, C-KNN

Abstract

Today many distinct products exists along with the configuration. Technology is advancing as well, proposed system deals with recommender system based on KNN clustering techniques. KNN along with filtering mechanism is introduced as a base mechanism to predict most likely products to be promoted through the recommender system. Simulation results indicates that the C-KNN (Content based K nearest neighbour technique is better than individual approaches of KNN and content based filtering.

References

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Published

2025-11-17
CITATION
DOI: 10.26438/ijcse/v6i10.136139
Published: 2025-11-17

How to Cite

[1]
J. Kaur, R. K. Bedi, and S. Gupta, “A Hybrid Approach for Performing Accurate prediction of Green Products using Recommender System”, Int. J. Comp. Sci. Eng., vol. 6, no. 10, pp. 137–139, Nov. 2025.

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Section

Research Article