Recommender Systems: The Textbook, Aggarwal Charu C.

Автор: Nikos Manouselis; Hendrik Drachsler; Katrien Verbe
Название: Recommender Systems for Technology Enhanced Learning
ISBN: 1493946560 ISBN-13(EAN): 9781493946563
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Collaborative Filtering Recommendation of Educational Content in Social Environments utilizing Sentiment Analysis Techniques.- Towards automated evaluation of learning resources inside repositories.- Linked Data and the Social Web as facilitators for TEL recommender systems in research and practice.- The Learning Registry: Applying Social Metadata for Learning Resource Recommendations.- A Framework for Personalised Learning-Plan Recommendations in Game-Based Learning.- An approach for an Affective Educational Recommendation Model.- The Case for Preference-Inconsistent Recommendations.- Further Thoughts on Context-Aware Paper Recommendations for Education.- Towards a Social Trust-aware Recommender for Teachers.- ALEF: from Application to Platform for Adaptive Collaborative Learning.- Two Recommending Strategies to enhance Online Presence in Personal Learning Environments.- Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem.- COCOON CORE: CO-Author Recommendations based on Betweenness Centrality and Interest Similarity.- Scientific Recommendations to Enhance Scholarly Awareness and Foster Collaboration.

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
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Цена: 16977.00 р.
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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: Panagiotis Symeonidis; Andreas Zioupos
Название: Matrix and Tensor Factorization Techniques for Recommender Systems
ISBN: 3319413562 ISBN-13(EAN): 9783319413563
Издательство: Springer
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Цена: 7685.00 р.
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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: Fatih Gedikli
Название: Recommender Systems and the Social Web
ISBN: 3658019476 ISBN-13(EAN): 9783658019471
Издательство: Springer
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Цена: 6986.00 р.
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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: Manouselis Nikos
Название: Recommender Systems for Technology Enhanced Learning
ISBN: 1493905295 ISBN-13(EAN): 9781493905294
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Recommender Systems for Technology Enhanced Learning

Название: Recommender systems
ISBN: 0367631857 ISBN-13(EAN): 9780367631857
Издательство: Taylor&Francis
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Цена: 15310.00 р.
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Описание: Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how theory is applied and implemented in actual 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: Francesco Ricci; Lior Rokach; Bracha Shapira
Название: Recommender Systems Handbook
ISBN: 1489977805 ISBN-13(EAN): 9781489977809
Издательство: Springer
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Цена: 25853.00 р.
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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: Felfernig
Название: Group Recommender Systems
ISBN: 3319750666 ISBN-13(EAN): 9783319750668
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This book presents group recommender systems, which focus on the determination of recommendations for groups of users. The book includes a discussion of basic group recommendation methods, aspects of human decision making in groups, and related applications.

Автор: Patricia Victor; Chris Cornelis; Martine De Cock
Название: Trust Networks for Recommender Systems
ISBN: 9491216392 ISBN-13(EAN): 9789491216398
Издательство: Springer
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Цена: 13974.00 р.
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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: Charu C. Aggarwal
Название: Recommender Systems
ISBN: 3319296574 ISBN-13(EAN): 9783319296579
Издательство: Springer
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Цена: 9362.00 р.
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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: Tarnowska Katarzyna, Ras Zbigniew W., Daniel Lynn
Название: Recommender System for Improving Customer Loyalty
ISBN: 3030134407 ISBN-13(EAN): 9783030134402
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book presents the Recommender System for Improving Customer Loyalty. The data mining techniques employed in the Recommender System allow users to "learn" from the experiences of others, without sharing proprietary information.