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Personalization Techniques And Recommender Systems

learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems.;

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Applied Recommender Systems with Python

as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as;

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Applied Recommender Systems with Python

as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as;

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User Modeling, Adaption, and Personalization

Personalization, held in Rome, Italy, in June 2013. The 21 long and 7 short papers of the research paper track were carefully reviewed and selected from;

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User Modeling, Adaptation, and Personalization

This book constitutes the refereed proceedings of the 20 th International Conference on User Modeling, Adaptation, and Personalization;

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User Modeling Adaptation and Personalization

This book constitutes the refereed proceedings of the 23rd International Conference on User Modeling, Adaptation and Personalization, UMAP;

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Hands-On Recommendation Systems with Python

you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to;

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Recommender Systems

systems and explain why certain recommendations are predicted over others. Techniques and approaches for developing recommender systems are;

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Practical Recommender Systems

Description Recommender systems are practically a necessity for keeping a site's content current, useful, and interesting to visitors;

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Building a Recommendation System with R

grips with the most important branches of recommendation * Understand various data processing and data mining techniques * Evaluate and;

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Social Network-Based Recommender Systems

This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link;

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Recommender Systems for Learning

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning;

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Adaptive Hypermedia and Adaptive Web-Based Systems

use of many person- ized systems, such as recommenders, personalized ?lters and retrieval systems, e-learning systems and various forms;

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Semantic Web Personalization and Context Awareness

Semantic Web Personalization and Context Awareness: Management of Personal Identities and Social Networking communicates relevant recent;

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Introduction to Data Science

field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and;

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Recommender System for Online Social Network

recommender systems, the relation between these research areas is still unclear. An innovative idea, which enables to integrate these areas, and;

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Recommender Systems in Fashion and Retail

This book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), and it aims to present a;

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Emotive and personality parameters in recommender systems

of a recommender system for images. The book will serve as a guideline and inspiration for practitioners and academics in content retrieval and;

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Towards Analytical Techniques for Systems Engineering Applications

This book is intended for specialists in systems engineering interested in new, general techniques and for students and practitioners;

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Towards Analytical Techniques for Systems Engineering Applications

This book is intended for specialists in systems engineering interested in new, general techniques and for students and practitioners;

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Human-Computer Interaction - INTERACT 2019

; methods for user studies; mobile HCI; personalization and recommender systems; pointing, touch, gesture and speech-based interaction techniques;

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Human-Computer Interaction - INTERACT 2019

; methods for user studies; mobile HCI; personalization and recommender systems; pointing, touch, gesture and speech-based interaction techniques;

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Recommender Systems

of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to;

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Recommender Systems

, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems;

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Semantics in Adaptive and Personalised Systems

apply such techniques in various use cases, such as recommender systems, user profiling and social media analysis. Throughout the book;

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Recommender Systems

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Active Learning for Recommender Systems

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