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Original Article
Product Recommendation System
Mohd. Abdul Jabbar1
Dr. Khaja Mahabubullah2
1Student, MCA Deccan College of Engineering and Technology, Hyderabad, Telangana, India. 2Professor & HOD, MCA Deccan College of Engineering and Technology, Hyderabad, Telangana, India.
Published Online: September-December 2025
Pages: 23-28
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250403005
References
1. J. Bobadilla, F. Ortega, A. Hernando, and A. Gutiérrez, "Recommender systems survey," Knowledge-Based Systems, vol. 46, pp. 109–132, Jul. 2013.
2. X. Su and T. M. Khoshgoftaar, "A survey of collaborative filtering techniques," Advances in Artificial Intelligence, vol. 2009, pp. 1–19, 2009.
3. A. Aggarwal, Recommender Systems: The Textbook. Springer, 2016.
4. P. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining, 2nd ed., Pearson Education, 2019.
5. D. M. Hawkins, "The problem of overfitting," Journal of Chemical Information and Computer Sciences, vol. 44, no. 1, pp. 1–12, Jan. 2004.
6. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2nd ed., Springer, 2009.
7. M. Steinbach, G. Karypis, and V. Kumar, "A comparison of document clustering techniques," Proc. KDD Workshop on Text Mining, vol. 400, no. 1, pp. 525–526, 2000.
8. D. MacKay, Information Theory, Inference, and Learning Algorithms. Cambridge University Press, 2003.
9. R. Kohavi and F. Provost, "Glossary of terms," Machine Learning, vol. 30, no. 2–3, pp. 271–274, 1998.
10. J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 3rd ed., Elsevier, 2011.
11. UCI Machine Learning Repository, "Online Retail Dataset," [Online]. Available: https://archive.ics.uci.edu/ml/datasets/online+retail [Accessed: Jun. 20, 2025].
12. Y. Zhao and G. Karypis, "Criterion functions for document clustering: Experiments and analysis," University of Minnesota, Department of Computer Science, Tech. Rep. 01-40, 2001.
13. S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme, "BPR: Bayesian personalized ranking from implicit feedback," in Proc. 25th Conf. on Uncertainty in Artificial Intelligence (UAI), 2009, pp. 452–461.
14. L. Rokach and B. Shapira, "Recommender systems: Introduction and challenges," in Recommender Systems Handbook, Springer, 2015, pp. 1–34.
15. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Eds., Recommender Systems Handbook. Springer, 2011.
2. X. Su and T. M. Khoshgoftaar, "A survey of collaborative filtering techniques," Advances in Artificial Intelligence, vol. 2009, pp. 1–19, 2009.
3. A. Aggarwal, Recommender Systems: The Textbook. Springer, 2016.
4. P. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining, 2nd ed., Pearson Education, 2019.
5. D. M. Hawkins, "The problem of overfitting," Journal of Chemical Information and Computer Sciences, vol. 44, no. 1, pp. 1–12, Jan. 2004.
6. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2nd ed., Springer, 2009.
7. M. Steinbach, G. Karypis, and V. Kumar, "A comparison of document clustering techniques," Proc. KDD Workshop on Text Mining, vol. 400, no. 1, pp. 525–526, 2000.
8. D. MacKay, Information Theory, Inference, and Learning Algorithms. Cambridge University Press, 2003.
9. R. Kohavi and F. Provost, "Glossary of terms," Machine Learning, vol. 30, no. 2–3, pp. 271–274, 1998.
10. J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 3rd ed., Elsevier, 2011.
11. UCI Machine Learning Repository, "Online Retail Dataset," [Online]. Available: https://archive.ics.uci.edu/ml/datasets/online+retail [Accessed: Jun. 20, 2025].
12. Y. Zhao and G. Karypis, "Criterion functions for document clustering: Experiments and analysis," University of Minnesota, Department of Computer Science, Tech. Rep. 01-40, 2001.
13. S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme, "BPR: Bayesian personalized ranking from implicit feedback," in Proc. 25th Conf. on Uncertainty in Artificial Intelligence (UAI), 2009, pp. 452–461.
14. L. Rokach and B. Shapira, "Recommender systems: Introduction and challenges," in Recommender Systems Handbook, Springer, 2015, pp. 1–34.
15. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Eds., Recommender Systems Handbook. Springer, 2011.
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