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Group Recommender Systems, 1st ed. 2018 An Introduction SpringerBriefs in Electrical and Computer Engineering Series

Langue : Anglais

Auteurs :

Couverture de l’ouvrage Group Recommender Systems
This book presents group recommender systems, which focus on the determination of recommendations for groups of users. The authors summarize different technologies and applications of group recommender systems. They include an in-depth discussion of state-of-the-art algorithms, an overview of industrial applications, an inclusion of the aspects of decision biases in groups, and corresponding de-biasing approaches. The book includes a discussion of basic group recommendation methods, aspects of human decision making in groups, and related applications. A discussion of open research issues is included to inspire new related research. The book serves as a reference for researchers and practitioners working on group recommendation related topics.
Part 1. Group Recommendation Techniques.- Decision Tasks and Basic Algorithms.- Algorithms for Group Recommendation.- Evaluating Group Recommender Systems.- Part 2. Group Recommender User Interfaces.- Group Recommender Applications.- Handling Preferences.- Explanations for Groups.- Part 3. Group Decision Processes.- Further Choice Scenarios.- Biases in Group Decisions.- Personality, Emotions, and Group Dynamics.- Conclusions.

Alexander Felfernig is a full professor at the Graz University of Technology (Austria) since March 2009 and received his PhD in Computer Science from the University of Klagenfurt. He directs the Applied Software Engineering (ASE) research group. His research interests include configuration systems, recommender systems, model-based diagnosis, software requirements engineering, different aspects of human decision making, and knowledge acquisition methods. In these areas, he is engaged in national research projects as well as in a couple of European Union projects. Alexander Felfernig has published numerous papers in renowned international conferences and journals (e.g., AI Magazine, Artificial Intelligence, IEEE Transactions on Engineering Management, IEEE Intelligent Systems, Journal of Electronic Commerce) and is a co-author of the book on "Recommender Systems" published by Cambridge University Press. He also acted as an organizer of international conferences and workshops such as the ACM International Conference on Recommender Systems and the International Symposium on Methodologies for Intelligent Systems and is currently a member of the Editorial Board of Applied Intelligence and the Journal of Intelligent Information Systems. With his research, he contributed to the development of commerical decision support and recommender systems such as ChoiclaWeb and EventHelpr.

Martin Stettinger studied Software Development and Business Economics at Graz, University of Technology and graduated in 2013 as MSc. with honors. He received his PhD in informatics in 2016 with honors.  At the moment, he is Senior Researcher at the Institute of Software Technology at Graz University of Technology, and co-founder and CTO of the 2013 founded SelectionArts Intelligent Decision Technologies Inc. The research focus of Martin Stettinger is in the field of recommender systems and includes recommendation-supported e-Learning, human decision making and highly person
Introduces the topic of group recommendation, presents an overview of existing industrial applications, and posits issues for future work Includes an in-depth overview of algorithms and techniques in group recommendation scenarios Includes a discussion of the role of human decision making strategies in the context of group decision making

Date de parution :

Ouvrage de 173 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

79,11 €

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