Social Network-Based Recommender Systems, Daniel Schall

Автор: Martin Atzmueller; Alvin Chin; Christoph Scholz; C
Название: Mining, Modeling, and Recommending `Things` in Social Media
ISBN: 3319147226 ISBN-13(EAN): 9783319147222
Издательство: Springer
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Цена: 5590.00 р.
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Описание: This book constitutes the thoroughly refereed joint post-workshop proceedings of the 4th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2013, held in Prague, Czech Republic, in September 2013, and the 4th International Workshop on Modeling Social Media, MSM 2013, held in Paris, France, in May 2013.

Автор: Gerald Kembellec; Ghislaine Chartron; Imad Saleh
Название: Recommender Systems
ISBN: 1848217684 ISBN-13(EAN): 9781848217683
Издательство: Wiley
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Цена: 22010.00 р.
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Описание: Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies.

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: Daniel Schall
Название: Social Network-Based Recommender Systems
ISBN: 3319372297 ISBN-13(EAN): 9783319372297
Издательство: Springer
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Цена: 11179.00 р.
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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: 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.