Library Recommendation System
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Abstract
Nowadays, the majority of online book retailers utilize their own recommendation engines to suggest books to their customers. Nonetheless, the majority of the times, the books that are suggested to users are irrelevant. This system aims to create a new strategy by utilizing the content-based filtering capability. This technique will result in a more refined and useful recommendation for the user. For testing reasons, a web-based prototype will be developed, and the system will be taught by feeding it data. Users will benefit from our recommendation system by having easier access to library materials and reduced resource waste.
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References
F.O. Isinkaye, Y.O. Folajimi, B.A. Ojokoh(2015), “Recommendation Systems: Principles, methods and evaluation, Egyptian Informatics Journal Vol. 16, pp. 261–273
Zhi Hui Wang and De Zhi Hou (2021), “Research on Book Recommendation Algorithm Based on Collaborative Filtering and Interest Degree”, Hindawi Wireless Communications and Mobile Computing, Volume 2021, Article ID 7036357, https://doi.org/10.1155/2021/7036357,pp. 1-7
E.Baatarjav, J.Chartree, and T. Meesumrarni (2010), “Group Recommendation System for Facebook”, 2010
J. Raymond. Mooney and R. Loriene (2012), “Content- Based Book Recommendation Using Learning for Text Categorization”, In proceedings of the fifth ACM conference on digital libraries, pp. 195- 204, San Antonio, TX
Mahiye Uluyagmur, Zehra Cataltepe and Esengul Tayfur (2012), “Content-Based Movie Recommendation Using Different Feature Sets”, Proceedings of the World Congress on Engineering and Computer Science ,Vol I ,WCECS 2012, October 24-26, San Francisco, USA
Sun Yachao, Han Fengxia(2015), “Research on Personalized recommendation system based on collaborative filtering algorithm”, Journal of Library Theory and Practice, Vol. 4, pp. 99-102
Ashlesha Bachhav , Apeksha Ukirade , Nilesh Patil , Manish Saswadkar , Prof. Nitin Shivale(2022), “Book Recommendation System using Machine learning and Collaborative Filtering “, International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), Vol. 2, Issue 1,pp. 279-283
Simon Philp, P. B. Shola et. al.(2014), “Application of Content-Based Approach in Research Paper Recommendation System for a Digital Library”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 5, No. 10, pp. 37-40
YongHong Tian et. al. (2019),”College Library Personalized Recommendation System based on Hybrid Recommendation Algorithm”, Elsevier, Science Direct, Procedia CIRP 83, pp. 490-494
“Anjali Sanjivanrao More et. al.(2022), “Book recommendation System using Machine Learning”, IJCRT, Vol. 10, Issue 5, ISSN: 2320-2882,pp. 39-43
Dhiman Sarma, Tanni Mittra , Mohammad Shahadat Hossain(2021) “Personalized Book Recommendation System using Machine Learning Algorithm”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 12, No. 1, pp. 212-219
Maryem Rhanoui , Mounia Mikram, Siham Yousfi , Ayoub Kasmi , Naoufel Zoubeidi(2022), “A hybrid recommender system for patron driven library acquisition and weeding”, Journal of King Saud University, Computer and Information Sciences, Vol. 34,pp. 2809–2819
Atish Bhosale, Komal Patil, Amruta Gaikwad, Riddhesh Deshmukh, Prof.S.S.Thigale (2022), “Book Recommendation System Using Machine Learning”, (IJAER) , Vol. No. 23, Issue No. V, May e-ISSN: 2231-5152, p-ISSN: 2454-1796
Esmael Ahmed and Adane Letta(2023), “Book Recommendation Using Collaborative Filtering Algorithm”, Hindawi Applied Computational Intelligence and Soft Computing, Vol. 2023, Article ID 1514801, https://doi.org/10.1155/2023/1514801,pp. 1-12
Yanping Du , Lizhi Peng , Shuihai Dou , Xianyang Su , and Xiaona Ren (2022), “Research on Personalized Book Recommendation Based on improved Similarity Calculation and Data Filling Collaborative filtering algorithm”, Hindawi Computational Intelligence and Neuroscience, Volume 2022, Article ID 1900209,https://doi.org/10.1155/2022/1900209, pp. 1-11
Anil Kumar, Sonal Chawla (2019), “Framework for Hybrid Book Recommender System based on Opinion Mining”, International Journal of Recent Technology and Engineering (IJRTE), ISSN: 2277-3878, Vol. 8 Issue 4,pp. 914-919
Aarush Gandhi et. al. (2022), “E-book recommendation system using content-based filtering”, ISSN: 2395-1303 http://www.ijetjournal.org, International Journal of Engineering and Techniques, Vol. 8 Issue 3, pp. 105-116
Shivam Goswami, Shobit Chowdhary,Shivam Mishra, Ajeet Singh (2023), “Book Recommendation System using Machine Learning”, International Journal of Innovative Science and Research Technology, Vol. 8, Issue 5, ISSN:2456-2165, pp. 816-818
Dhanashri Wadikar, Nandani Kumari, Ranjana Bhat, Vaishali Shirodkar (2020), “Book Recommendation Platform using Deep Learning”, IJRET, Vol. 07, Issue: 06, p-ISSN: 2395-0072, pp. 6764-6770
E. Uko Okon, B. O. Eke, O. Asagba (2018), “An Improved Online Book Recommender System using Collaborative Filtering Algorithm”, International Journal of Computer Applications (0975 – 8887), Vol. 179 , No.46, pp. 41-48
M. V. Kumar, P.N.V.S. Pawan Kumar (2019), “A Study on Different Phases and Various Recommendation System Techniques”, International Journal of Recent Technology and Engineering, Vol. 7, Issue 5C, pp. 38-41.