Tag: Recommender

Persuasive Recommender Systems Conceptual Background and Implications


Free Download Persuasive Recommender Systems: Conceptual Background and Implications By Kyung-Hyan Yoo, Ulrike Gretzel, Markus Zanker (auth.)
2013 | 59 Pages | ISBN: 1461447011 | PDF | 1 MB
Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding influential factors in advice seeking relationships, which is abundant in the context of human-human relationships, can provide an important framework for identifying potential influence factors in recommender system context. This book reviews the existing literature on the factors in advice seeking relationships in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

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Recommender Systems Frontiers and Practices


Free Download Recommender Systems: Frontiers and Practices by Dongsheng Li, Jianxun Lian, Le Zhang
English | March 26, 2024 | ISBN: 9819989639 | 296 pages | MOBI | 17 Mb
This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft ‘s open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch.

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Trust Networks for Recommender Systems


Free Download Trust Networks for Recommender Systems By Patricia Victor, Chris Cornelis, Martine de Cock (auth.)
2011 | 202 Pages | ISBN: 9491216074 | PDF | 5 MB
This book describes research performed in the context of trust/distrust propagation and aggregation, and their use in recommender systems. This is a hot research topic with important implications for various application areas. The main innovative contributions of the work are: -new bilattice-based model for trust and distrust, allowing for ignorance and inconsistency -proposals for various propagation and aggregation operators, including the analysis of mathematical properties -Evaluation of these operators on real data, including a discussion on the data sets and their characteristics. -A novel approach for identifying controversial items in a recommender system -An analysis on the utility of including distrust in recommender systems -Various approaches for trust based recommendations (a.o. base on collaborative filtering), an in depth experimental analysis, and proposal for a hybrid approach -Analysis of various user types in recommender systems to optimize bootstrapping of cold start users.

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Session-Based Recommender Systems Using Deep Learning


Free Download Session-Based Recommender Systems Using Deep Learning
English | 2024 | ISBN: 3031425588 | 314 Pages | PDF (True) | 29 MB
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.

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Group Recommender Systems An Introduction (2nd Edition)


Free Download Group Recommender Systems: An Introduction
English | 2024 | ISBN: 3031449428 | 324 Pages | PDF EPUB (True) | 10 MB
This book discusses different aspects of group recommender systems, which are systems that help to identify recommendations for groups instead of single users. In this context, the authors present different related techniques and applications. The book includes in-depth summaries of group recommendation algorithms, related industrial applications, different aspects of preference construction and explanations, user interface aspects of group recommender systems, and related psychological aspects that play a crucial role in group decision scenarios.

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