Recommender Systems for Information Providers (eBook)

Designing Customer Centric Paths to Information

Andreas W. Neumann (Autor)

eBook Download: PDF

2009
X, 158 Seiten
Physica (Verlag)
978-3-7908-2134-5 (ISBN)

Infos

Information providers are a very promising application area of recommender systems due to the general problem of assessing the quality of information products prior to the purchase. Recommender systems automatically generate product recommendations: customers profit from a faster finding of relevant products, stores profit from rising sales. All aspects of recommender systems are covered: the economic background, mechanism design, a survey of systems in the Internet, statistical methods and algorithms, service oriented architectures, user interfaces, as well as experiences and data from real-world applications. Specific solutions for areas with strong privacy concerns, scalability issues for large collections of products, as well as algorithms to lessen the cold-start problem for a faster return on investment of recommender projects are addressed. This book describes all steps it takes to design, implement, and successfully operate a recommender system for a specific information platform.

Inhalt

Preface 5
Contents 7
1 Introduction 11
1.1 Recommender Systems 11
1.2 Scienti.c and Technical Information 14
1.3 Motivation and Focus 16
1.4 Chapter Guide 18
2 The Market of Scienti.c and Technical Information 19
2.1 Information Providers in the Digital Age 19
2.2 The 2-3-6-Value-Chain for STI Markets 24
2.3 The Strategic Positions of the Market Players 26
2.4 Recommender Systems in the Business Pro.le of Information Providers 31
3 Classi.cation and Mechanism Design of Recommender Systems 32
3.1 Classi.cations of Recommender Systems 32
3.2 Mechanism Design 35
4 A Survey of Recommender Systems at Major STI Providers 40
4.1 Scienti.c Libraries 40
4.2 Scienti.c Projects 44
4.3 E-Commerce: Amazon.com 45
4.4 Social Tagging 48
5 Case Study: Explicit Recommender Services for Scienti.c Libraries 52
5.1 General Setup 52
5.2 Rating Service 56
5.3 Review Service 57
5.4 Usage Statistics 59
5.5 Discussion 60
6 General Concepts of Behavior-Based Recommender Services 65
6.1 Revealed Preference Theory and Choice Sets 65
6.2 Self-Selection 67
6.3 Prices, Transaction Costs, Market Baskets, Lending Data, and Browser Sessions 67
6.4 Knowledge Discovery and Data Mining 69
6.5 Observed Users vs. Target Group of Recommendations 69
6.6 Factors for the Di.usion of Recommendations 70
7 Algorithms for Behavior-Based Recommender Systems 72
7.1 Purchase Noise Filtering by Means of the Logarithmic Series Distribution 72
7.2 POSICI and POMICI: Recommendations from Small Samples 83
7.3 Related Methods 94
8 Case Study: Behavior-Based Recommender Services for Scienti.c Libraries 97
8.1 Service Description 97
8.2 Implementation 103
8.3 Evaluation 112
8.4 BibTip: Commercial Implicit Recommendation Services for Libraries 121
8.5 Extensions, Improvements, and Further Applications 122
9 Visualizing and Exploring Information Spaces 126
9.1 A Survey of Visual Interfaces to Information Providers 127
9.2 RecoDiver: A Graph-Based User Interface to Recommendations 129
9.3 Evaluation 135
9.4 Discussion and Outlook 137
10 Discussion 139
List of Figures 143
List of Tables 146
References 147

Produkt-Details

• Erscheint lt. Verlag: 3.3.2009
• Reihe/Serie: Contributions to Management Science
• Reihe/Serie: Contributions to Management Science
• Zusatzinfo: X, 158 p. 47 illus.
• Verlagsort: Heidelberg
• Sprache: englisch
• Themenwelt: Geisteswissenschaften ► Sprach- / Literaturwissenschaft
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Wirtschaft ► Allgemeines / Lexika
• Schlagworte: classification • Consumer buying behavior • E-Commerce • Internet • libraries • Scientific Information • Web 2.0
• ISBN-10: 3-7908-2134-9 / 3790821349
• ISBN-13: 978-3-7908-2134-5 / 9783790821345