Recommender Systems in Fashion and Retail, Dokoohaki Nima, Jaradat Shatha, Corona Pampнn Humberto Jesъs
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: 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: Ras Zbigniew W., Wieczorkowska Alicja, Tsumoto Shusaku Название: Recommender Systems for Medicine and Music ISBN: 3030664481 ISBN-13(EAN): 9783030664480 Издательство: Springer Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Music recommendation systems are becoming more and more popular. Listening to music may improve heart rate, respiratory rate, and blood pressure in people with heart disease. The book presents a variety of approaches useful to create recommendation systems in healthcare, music, and in music therapy.
Автор: Panagiotis Symeonidis; Andreas Zioupos Название: Matrix and Tensor Factorization Techniques for Recommender Systems ISBN: 3319413562 ISBN-13(EAN): 9783319413563 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step-by-step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods.
Автор: Panagiotis Symeonidis; Dimitrios Ntempos; Yannis M Название: Recommender Systems for Location-based Social Networks ISBN: 1493902857 ISBN-13(EAN): 9781493902859 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Recommender Systems.- Online Social Networks.- Location-based Social Networks.- Framework.- Algorithms.- Comparison.- Real Geo-social Recommender Systems.- Conclusions.
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: 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.
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Автор: Francesco Ricci; Lior Rokach; Bracha Shapira Название: Recommender Systems Handbook ISBN: 1489977805 ISBN-13(EAN): 9781489977809 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recommender Systems: Introduction and Challenges.- A Comprehensive Survey of Neighborhood-based Recommendation Methods.- Advances in Collaborative Filtering.- Semantics-aware Content-based Recommender Systems.- Constraint-based Recommender Systems.- Context-Aware Recommender Systems.- Data Mining Methods for Recommender Systems.- Evaluating Recommender Systems.- Evaluating Recommender Systems with User Experiments.- Explaining Recommendations: Design and Evaluation.- Recommender Systems in Industry: A Netflix Case Study.- Panorama of Recommender Systems to Support Learning.- Music Recommender Systems.- The Anatomy of Mobile Location-Based Recommender Systems.- Social Recommender Systems.- People-to-People Reciprocal Recommenders.- Collaboration, Reputation and Recommender Systems in Social Web Search.- Human Decision Making and Recommender Systems.- Privacy Aspects of Recommender Systems.- Source Factors in Recommender System Credibility Evaluation.- Personality and Recommender Systems.- Group Recommender Systems: Aggregation, Satisfaction and Group Attributes.- Aggregation Functions for Recommender Systems.- Active Learning in Recommender Systems.- Multi-Criteria Recommender Systems.- Novelty and Diversity in Recommender Systems.- Cross-domain Recommender Systems.- Robust Collaborative Recommendation.
Автор: Jos? J. Pazos Arias; Ana Fern?ndez Vilas; Rebeca P Название: Recommender Systems for the Social Web ISBN: 3642446272 ISBN-13(EAN): 9783642446276 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces opportunities and challenges that arise in the recommenders` area with the advent of Web 2.0. It presents the mains aspects in the Web 2.0 hype which have to be incorporated in traditional recommender systems.
Автор: Fatih Gedikli Название: Recommender Systems and the Social Web ISBN: 3658019476 ISBN-13(EAN): 9783658019471 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: ГЇВїВЅ There is an increasing demand for recommender systems due to the information overload users are facing on the Web. A tag recommender algorithm is proposed which recommends tags for users to annotate their favorite online resources.
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.
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