Recommender Systems for Location-based Social Networks, Panagiotis Symeonidis; Dimitrios Ntempos; Yannis M
Автор: Sachi Nandan Mohanty; Jyotir Moy Chatterjee Название: Recommender system with machine learning and artificial intelligence : ISBN: 1119711576 ISBN-13(EAN): 9781119711575 Издательство: Wiley Рейтинг: Цена: 28979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising.
This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare 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.
This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.
Автор: Patricia Victor; Chris Cornelis; Martine De Cock Название: Trust Networks for Recommender Systems ISBN: 9491216392 ISBN-13(EAN): 9789491216398 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Featuring innovative contributions to the field such as a new bilattice-based model for trust and distrust, this book on a hot research topic is the first in-depth study of the potential of distrust in the emerging domain of trust-enhanced recommendation.
Автор: Daniel Schall Название: Social Network-Based Recommender Systems ISBN: 3319227343 ISBN-13(EAN): 9783319227344 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems.
Автор: Daniel Schall Название: Social Network-Based Recommender Systems ISBN: 3319372297 ISBN-13(EAN): 9783319372297 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems.
Автор: Dokoohaki Nima, Jaradat Shatha, Corona Pampнn Humberto Jesъs Название: Recommender Systems in Fashion and Retail ISBN: 3030661024 ISBN-13(EAN): 9783030661021 Издательство: Springer Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1. The Importance of Brand Affinity in Luxury Fashion Recommendations.- Chapter 2. Probabilistic Color Modelling of Clothing Items.- Chapter 3. User Aesthetics Identification for Fashion Recommendations.- Chapter 4. Towards User-in-the-Loop Online Fashion Size Recommendation with Low Cognitive Load.- Chapter 5. Attention Gets You the Right Size and Fit in Fashion.- Chapter 6. The Ensemble-Building Challenge for Fashion Recommendation.- Chapter 7. Outfit Generation and Recommendation - An Experimental Study.- Chapter 8. Understanding Professional Fashion Stylists' Outfit Recommendation Process.
Описание: Provides a comprehensive review of state-of-the-art practices for ERS, as well as the challenges to achieve their actual deployment. It will help covers researchers interested in recommendation strategies for educational scenarios and in evaluating the impact of recommendations in learning, as well as academics and practitioners in the area of technology enhanced learning.
Автор: Negre Название: Information and Recommender Systems ISBN: 1848217544 ISBN-13(EAN): 9781848217546 Издательство: Wiley Рейтинг: Цена: 22010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Information is an element of knowledge that can be stored, processed or transmitted. It is linked to concepts of communication, data, knowledge or representation. In a context of steady increase in the mass of information it is difficult to know what information to look for and where to find them.
Автор: Guang-quan Zhang, Jie Lu, Qian Zhang Название: Recommender Systems: Advanced Developments ISBN: 9811224625 ISBN-13(EAN): 9789811224621 Издательство: World Scientific Publishing Рейтинг: Цена: 19800.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recommender systems provide users (businesses or individuals) with personalized online recommendations of products or information, to address the problem of information overload and improve personalized services. Recent successful applications of recommender systems are providing solutions to transform online services for e-government, e-business, e-commerce, e-shopping, e-library, e-learning, e-tourism, and more.This unique compendium not only describes theoretical research but also reports on new application developments, prototypes, and real-world case studies of recommender systems. The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems — basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications.By providing state-of-the-art knowledge, this excellent reference text will immensely benefit researchers, managers, and professionals in business, government, and education to understand the concepts, methods, algorithms and application developments in recommender systems.
Автор: Dokoohaki Nima Название: Fashion Recommender Systems ISBN: 3030552179 ISBN-13(EAN): 9783030552176 Издательство: Springer Цена: 23757.00 р. Наличие на складе: Поставка под заказ.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
Автор: Charu C. Aggarwal Название: Recommender Systems ISBN: 3319296574 ISBN-13(EAN): 9783319296579 Издательство: Springer Рейтинг: Цена: 9362.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An Introduction to Recommender Systems.- Neighborhood-Based Collaborative Filtering.- Model-Based Collaborative Filtering.- Content-Based Recommender Systems.- Knowledge-Based Recommender Systems.- Ensemble-Based and Hybrid Recommender Systems.- Evaluating Recommender Systems.- Context-Sensitive Recommender Systems.- Time- and Location-Sensitive Recommender Systems.- Structural Recommendations in Networks.- Social and Trust-Centric Recommender Systems.- Attack-Resistant Recommender Systems.- Advanced Topics in Recommender Systems.
Автор: Aggarwal Charu C. Название: Recommender Systems: The Textbook ISBN: 331980619X ISBN-13(EAN): 9783319806198 Издательство: Springer Рейтинг: Цена: 9362.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An Introduction to Recommender Systems.- Neighborhood-Based Collaborative Filtering.- Model-Based Collaborative Filtering.- Content-Based Recommender Systems.- Knowledge-Based Recommender Systems.- Ensemble-Based and Hybrid Recommender Systems.- Evaluating Recommender Systems.- Context-Sensitive Recommender Systems.- Time- and Location-Sensitive Recommender Systems.- Structural Recommendations in Networks.- Social and Trust-Centric Recommender Systems.- Attack-Resistant Recommender Systems.- Advanced Topics in Recommender Systems.
First designed to generate personalized recommendations to users in the 90s, recommender systems apply knowledge discovery techniques to users' data to suggest information, products, and services that best match their preferences. In recent decades, we have seen an exponential increase in the volumes of data, which has introduced many new challenges.
Divided into two volumes, this comprehensive set covers recent advances, challenges, novel solutions, and applications in big data recommender systems. Volume 1 contains 14 chapters addressing foundations, algorithms and architectures, approaches for big data, and trust and security measures. Volume 2 covers a broad range of application paradigms for recommender systems over 23 chapters.
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