Approach to Building a Book Recommendation System

References

[1] Bobadilla, J., Ortega, F., & Hernando, A. (2013). Recommender systems survey. Knowledge-Based Systems, 46, 109-132.

[2] Covington, P., Adams, J., &Sargin, E. (2016). Deep neural networks for youtube recommendations. In Proceedings of the 10th ACM Conference on Recommender Systems (pp. 191-198). ACM.

[3] Herlocker, J. L., Konstan, J. A., Terveen, L. G., &Riedl, J. T. (2004). Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems (TOIS), 22(1), 5-53.

[4] Koren, Y., Bell, R., &Volinsky, C. (2009). Matrix factorization techniques for recommender systems. Computer, 42(8), 30-37.

[5] Lops, P., Gemmis, M., & Semeraro, G. (2011). Content-based recommendation systems. In Recommender systems handbook (pp. 73-105). Springer, Boston, MA.

[6] Pazzani, M. J., &Billsus, D. (2007). Content-based recommendation systems. In The adaptive web (pp. 325-341). Springer, Berlin, Heidelberg.

[7] Resnick, P., & Varian, H. R. (1997). Recommender systems. Communications of the ACM, 40(3), 56-58.

[8] Zhang, Y., Li, X., & Cheng, X. (2018). Deep learning for recommender systems: A survey. ACM Computing Surveys (CSUR),

[9] Sarma, Dhiman &Mittra, Tanni& Shahadat, Mohammad. (2021). Personalized Book Recommendation System using Machine Learning Algorithm. International Journal of Advanced Computer Science and Applications. 12. 10.14569/IJACSA.2021.0120126.

[10] Beel, Joeran, et al. “Research-paper Recommender Systems: A Literature Survey - International Journal on Digital Libraries.” SpringerLink, 26 July 2015, link.springer.com/article/10.1007/s00799-015-0156-0

[11] Wan, Mengting, et al. “Fine-Grained Spoiler Detection From Large-Scale Review Corpora.” ACL Anthology, 31 May 2019, aclanthology.org/P19-1248.

[12] Mengting Wan and Julian McAuley. 2018. Item recommendation on monotonic behavior chains. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys '18). Association for Computing Machinery, New York, NY, USA, 86–94. https://doi.org/10.1145/3240323.3240369

[13] (2011). TF–IDF. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_832

[14] Singhal, Amit. Modern Information Retrieval: A Brief Overview. singhal.info/ieee2001.pdf.

[15] Brin, S. B., & Page, L. P. (n.d.). The Anatomy of a Large-Scale Hypertextual Web Search Engine.

[16] Noy, N. (2019b). Google Dataset Search: Building a search engine for datasets in an open Web ecosystem –. Google Research. Retrieved October 17, 2022, from https://research.google/pubs/pub47845/

[17] Sharifi, Zeinab &Rezghi, Mansoor &Nasiri, Mahdi. (2013). New algorithm for recommender systems based on singular value decomposition method. Proceedings of the 3rd International Conference on Computer and Knowledge Engineering, ICCKE 2013. 86-91. 10.1109/ICCKE.2013.6682799.

@article{1703987,
      author = {Jayank Tyagi, Vandana Choudhary, Namita Goyal},
      title = {Approach to Building a Book Recommendation System},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {7},
      pages = {30-36},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703987.pdf},
      abstract = {Every day, the Internet gets smarter. Your favourite websites seem to have a premonition of what you'll like before you've even seen it. The item you may have forgotten or meant to add before checking out is almost magically discovered by the online shopping cart that is keeping your purchases. These web applications seem to read your mind, but do they really? It seems that more arithmetic than magic is involved in anticipating a user's preferences. While a lot of people and companies struggled in 2020, book publishers only saw a slight decline and actually witnessed growth in many areas. People searching for ways to combat anxiety and boredom when confined indoors turned to the tried-and-true remedy of literature. In 2021, reading improved, with voracious readers consuming more books overall. So, with this project we decided to apply this seemingly magical technique of recommendations to one of the most conventional forms of media which is books.},
      keywords = {Internet, Websites, Online shopping, Web applications, User preferences, Book publishers, Reading, Recommendations, Media, Books},
      month = {January},
  }