Description: Group Recommender Systems by Alexander Felfernig, Ludovico Boratto, Martin Stettinger, Marko Tkalčič Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book discusses different aspects of group recommender systems, which are systems that help to identify recommendations for groups instead of single users. Publisher Description This book discusses different aspects of group recommender systems, which are systems that help to identify recommendations for groups instead of single users. In this context, the authors present different related techniques and applications. The book includes in-depth summaries of group recommendation algorithms, related industrial applications, different aspects of preference construction and explanations, user interface aspects of group recommender systems, and related psychological aspects that play a crucial role in group decision scenarios. Author Biography 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 machine learning. 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 User Modeling and User-Adapted Interaction) and is a co-author of the book on "Recommender Systems" published by Cambridge University Press. He also acted as an organizer of internationalconferences such as the ACM International Conference on Recommender Systems,the International Symposium on Methodologies for Intelligent Systems, and the ACM International Systems and Software Product Line Conference, and is 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.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 Computer Science 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 personalized software systems. These topics include recommendation technologies for group decision tasks, different aspects of human learning and decision making behaviour as well as different methods of knowledge acquisition. He published over 90 publications at international workshops, conferences, and journals. He has long-term experience in software projects and special expertise in the areas of mobile devices, Web-programming, and Web-applications.Ludovico Boratto is a researcher at the Department of Mathematics and Computer Science of the University of Cagliari (Italy). His research interests focus on recommender systems and their impact on the different stakeholders, both considering accuracy and beyond-accuracy evaluation metrics. He has authored more than 60 papers and published his research in top-tier conferences and journals. His research activity also brought him to give talks and tutorials at top-tier conferences and research centers (Yahoo! Research). He is editor of the book "Group Recommender Systems: An Introduction", published by Springer. He is an editorial board member of the "Information Processing & Management" journal (Elsevier) and "Journal of Intelligent Information Systems" (Springer), and guest editor of several journals special issues. He is regularly part of the program committees of the main Web conferences, where he received four outstanding contribution awards. In 2012, he got his Ph.D. at the University of Cagliari (Italy), where he was a research assistant until May 2016. From May 2016 to April 2021, he joined Eurecat as Senior Research Scientist in the Data Science and Big Data Analytics research group. In 2010 and 2014, he spent ten months at Yahoo! Research in Barcelona as a visiting researcher. He is a member of ACM and IEEE. Marko Tkali is associate professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He aims at improving personalized services (e.g. recommender systems) through the usage of psychological models in personalization algorithms. To achieve this, he uses diverse research methodologies, including data mining, machine learning, and user studies. He is editorial board member of the Springer UMUAI journal. He served as Program Chair at the ACM UMAP 2021 conference. Details ISBN 3031449428 ISBN-13 9783031449420 Title Group Recommender Systems Author Alexander Felfernig, Ludovico Boratto, Martin Stettinger, Marko Tkalčič Format Hardcover Year 2023 Pages 181 Edition 2nd Publisher Springer International Publishing AG GE_Item_ID:158867855; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 114.57 USD
Location: Fairfield, Ohio
End Time: 2024-11-27T07:25:56.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9783031449420
Book Title: Group Recommender Systems
Number of Pages: Xi, 181 Pages
Language: English
Publication Name: Group Recommender Systems : an Introduction
Publisher: Springer
Publication Year: 2023
Subject: Probability & Statistics / General, Library & Information Science / General, Telecommunications, Databases / Data Mining
Type: Textbook
Item Weight: 16.4 Oz
Author: Ludovico Boratto
Subject Area: Mathematics, Computers, Technology & Engineering, Language Arts & Disciplines
Item Length: 9.3 in
Series: Signals and Communication Technology Ser.
Item Width: 6.1 in
Format: Hardcover
