Recommender Systems: The Textbook Charu C. Aggarwal pdf english

Recommender Systems: The Textbook

Computers & Internet, Charu C. Aggarwal

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Recommender Systems: The Textbook Charu C. Aggarwal pdf english - Le téléchargement de ce bel Recommender Systems: The Textbook livre et le lire plus tard. Êtes-vous curieux, qui a écrit ce grand livre? Oui, Charu C. Aggarwal est l'auteur pour Recommender Systems: The Textbook. Ce livre se composent de plusieurs pages 325. Charu C. Aggarwal est la société qui libère Recommender Systems: The Textbook au public. est la date de lancement pour la première fois. Lire l'Recommender Systems: The Textbook maintenant, il est le sujet plus intéressant. Toutefois, si vous ne disposez pas de beaucoup de temps à lire, vous pouvez télécharger Recommender Systems: The Textbook à votre appareil et vérifier plus tard.. Si vous avez décidé de trouver ou lire ce livre, ci-dessous sont des informations sur le détail de Recommender Systems: The Textbook pour votre référence.

de Charu C. Aggarwal

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This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories:

Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation.

Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored.

Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed.

In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications.

Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.Classement des meilleures ventes d'Amazon : 454081
Manufacturer : Springer

Si vous avez un intérêt pour Recommender Systems: The Textbook, vous pouvez également lire un livre similaire tel que cc Statistical Methods for Recommender Systems, Artificial Intelligence: A Modern Approach, Global Edition, Deep Learning, Convex Optimization, Data Science : fondamentaux et études de cas: Machine Learning avec Python et R, Probabilistic Graphical Models: Principles and Techniques