مورد إلكتروني
Favorite Book Prediction System Using Machine Learning Algorithms
| العنوان: | Favorite Book Prediction System Using Machine Learning Algorithms |
|---|---|
| المصدر: | Journal of Applied Engineering and Technological Science (JAETS); Vol. 4 No. 2 (2023): Journal of Applied Engineering and Technological Science (JAETS); 983-991; 2715-6079; 2715-6087; 10.37385/jaets.v4i2 |
| بيانات النشر: | Yayasan Riset dan Pengembangan Intelektual (YRPI) 2023-06-05 |
| تفاصيل مُضافة: | Daimari, Dersin Mondal, Subhash Brahma, Bihung Nag, Amitava |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Recent years have seen the rapid deployment of Artificial Intelligence (AI) which allows systems to take intelligent decisions. AI breakthroughs could radically change modern libraries' operations. However, introducing AI in modern libraries is a challenging task. This research explores the potential for smart libraries to improve the caliber of user services through the use of machine learning (ML) techniques. The proposed work investigates machine learning methods such as Random Forest (RF) and boosting algorithms, including Light Gradient Boosting Machine (LGBM), Histogram-based gradient boosting (HGB), Extreme gradient boosting (XGB), CatBoost (CB), AdaBoost (AB), and Gradient Boosting (GB) for the task of identifying and classifying Favorite books and compares their performances. Comprehensive experiments performed on the publicly available dataset (Art Garfunkel's Library) show that the proposed model can effectively handle the task of identifying and classifying Favorite books. Experimental results show that LGBM has achieved outstanding performance with an accuracy rate of 94.9367% than Random Forest and other boosting ML algorithms. This empirical research work takes advantage of AI adoption in libraries using machine learning techniques. To the best of our knowledge, we are the first to develop an intelligent application for the modern library to automatically identify and classify Favorite books |
| مصطلحات الفهرس: | Machine Learning, artificial intelligence (AI), Smart Library, Light Gradient Boosting Machine (LGBM), Boosting Model, info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion, Peer-reviewed Article |
| URL: | |
| الإتاحة: | Open access content. Open access content Copyright (c) 2023 Journal of Applied Engineering and Technological Science (JAETS) |
| ملاحظة: | application/pdf English |
| أرقام أخرى: | IDRID oai:ojs2.journal.yrpipku.com:article/1925 10.37385/jaets.v4i2.1925 1390109564 |
| المصدر المساهم: | RESEARCH & INTELLECTUAL DEV FOUND From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1390109564 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |