| 书目名称 | Session-Based Recommender Systems Using Deep Learning | | 编辑 | Reza Ravanmehr,Rezvan Mohamadrezaei | | 视频video | | | 概述 | Elaborates concepts and fundamentals of session-based recommender systems.Presents the usage of using deep learning techniques in session-based recommender systems from different perspectives.Aims at | | 图书封面 |  | | 描述 | .This book focuses on the widespread use of deep neural networks and their various techniques in session-based recommender systems (SBRS). It presents the success of using deep learning techniques in many SBRS applications from different perspectives. For this purpose, the concepts and fundamentals of SBRS are fully elaborated, and different deep learning techniques focusing on the development of SBRS are studied...The book is well-modularized, and each chapter can be read in a stand-alone manner based on individual interests and needs. In the first chapter of the book, definitions and concepts related to SBRS are reviewed, and a taxonomy of different SBRS approaches is presented, where the characteristics and applications of each class are discussed separately. The second chapter starts with the basic concepts of deep learning and the characteristics of each model. Then, each deep learning model, along with its architecture and mathematical foundations, is introduced. Next, chapter 3 analyses different approaches of deep discriminative models in session-based recommender systems. In the fourth chapter, session-based recommender systems that benefit from deep generative neural netw | | 出版日期 | Book 2024 | | 关键词 | Recommender Systems; Deep Learning; Machine Learning; Social Network Analysis; Big Data Analysis | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-42559-2 | | isbn_softcover | 978-3-031-42561-5 | | isbn_ebook | 978-3-031-42559-2 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 18:11:47
