Beschreibung Recommender Systems: An Introduction. In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems.
Recommender Systems: An Introduction 1st edition by ~ Recommender Systems: An Introduction 1st edition by Jannach, Dietmar, Zanker, Markus, Felfernig, Alexander, Frie (2010) Gebundene Ausgabe / Jannach, Dietmar, Zanker, Markus, Felfernig, Alexander, Frie / ISBN: / Kostenloser Versand fĂŒr alle BĂŒcher mit Versand und Verkauf duch . Zum Hauptinhalt wechseln. Prime entdecken DE Hallo! Anmelden Konto und Listen Anmelden Konto und Listen .
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Recommender Systems: An Introduction Author: Dietmar ~ [(Recommender Systems: An Introduction )] [Author: Dietmar Jannach] [Nov-2010] / Dietmar Jannach / ISBN: / Kostenloser Versand fĂŒr alle BĂŒcher mit Versand und Verkauf duch .
Recommender Systems An introduction ~ Recommender Systems An introduction Dietmar Jannach, TU Dortmund, Germany Slides presented at PhD School 2014, University Szeged, Hungary dietmar.jannach@tu-dortmund. 2 Recommender Systems. 3 In e-commerce. 4 In Social Media. 5 Apps .. 6 Entertainment. 7 And even more. 8 Limitations. 9 Computational advertising ⊠10 Will give you an introduction to the field of Recommender Systems How can .
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[PDF] Recommender Systems - An Introduction / Semantic Scholar ~ Recommender Systems - An Introduction @inproceedings{Jannach2010RecommenderS, title={Recommender Systems - An Introduction}, author={D. Jannach and M. Zanker and A. Felfernig and G. Friedrich}, year={2010} } D. Jannach, M. Zanker, +1 author G. Friedrich; Published 2010; Computer Science; In this age of information overload, people use a variety of strategies to make choices about what to buy .
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Recommender Systems - The Textbook / Charu C. Aggarwal ~ This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book .
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Recommender Systems ~ Contents 1 An Introduction to Recommender Systems 1 1.1 Introduction ... 1 1.2 GoalsofRecommenderSystems ... 3
Recommender Systems â An Introduction â Teaching Material ~ Powerpoint-Slides for Recommender Systems - An Introduction. Chapter 01 - Introduction (756 KB) - PDF (466 KB) Chapter 02 - Collaborative recommendation (2.063 KB) - PDF (1.188 KB) Chapter 03 - Content-based recommendation (806 KB) - PDF (590 KB) Chapter 04 - Knowledge-based recommendation (1.321 KB) - PDF (1.152 KB) Chapter 05 - Hybrid recommendation approaches (294 KB) - PDF (368 KB) Chapter .
Tutorial: Recommender Systems ~ Recommender systems implementation & evaluation Product configuration systems Web mining Operations research-7-© Dietmar Jannach, Markus Zanker and Gerhard Friedrich Agenda What are recommender systems for? â Introduction How do they work (Part I) ? â Collaborative Filtering How to measure their success? â Evaluation techniques How do they work (Part II) ? âContentâbased Filtering .
Recommender Systems / SpringerLink ~ This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book .
An Introduction to Recommender Systems / SpringerLink ~ An introduction to recommender systems, Cambridge University Press, 2011. Google Scholar [291] M. Kaminskas and F. Ricci. Contextual music information retrieval and recommendation: State of the art and challenges. Computer Science Review, 6(2), pp. 89â119, 2012. CrossRef Google Scholar [297] D. Kempe, J. Kleinberg, and E. Tardos. Maximizing the spread of influence through a social network .
Recommender Systems Handbook / Francesco Ricci / Springer ~ Recommender Systems Handbook, an edited volume, 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. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims .
Recommender Systems by Dietmar Jannach ~ Recommender Systems An Introduction. Get access. Buy the print book Check if you have access via personal or institutional login . Log in Register Recommend to librarian Cited by 257; Cited by. 257. Crossref Citations. This book has been cited by the following publications. This list is generated based on data provided by CrossRef. Zanker, Markus and Ninaus, Daniel 2010. Knowledgeable .
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