Beschreibung
Inhaltsangabe1 Introduction and Motivation 1.1 Motivation 1.2 Objectives 1.3 The Outline of the Thesis 2 Background and Related Work 2.1 A Parsimonious Overview of Recommendation Techniques 2.2 Explanations in Recommender Systems 2.3 MovieRelated Preferences and Relevant Movie Characteristics 2.4 Summary 3 Conceptual Framework of a Hybrid Recommender System that allows for Effective Explanations of Recommendations 3.1 The Modeling of User Preferences 3.2 The Estimation of Model Parameters 3.3 Hybridization with Collaborative Filtering 4 Empirical Study 4.1 The Examined Datasets and Their Properties 4.2 Measures of Prediction Accuracy 4.3 The Employed Algorithms and Benchmarks 4.4 Results 4.5 Summary 5 Conclusions and Future Work 5.1 Research Summary, Key Findings and Contributions 5.2 Discussion and Implications 5.3 Limitations and Avenues for Future Research
Autorenporträt
Paul Marx, born in Novosibirsk (Russia) in 1979, studied Aero-hydrodynamics and Business Administration at the Novosibirsk State Technical University. From 1998 to 2000 he worked as marketing director at Siberian ration supply company "Vital Ltd.". He moved to Germany in 2000, where he continued his studies in Business Administration at the University of Hannover and obtained a master's degree (Dipl.-Ök.) in 2006, specializing in marketing, media research, and economic computer science. At the same time he founded a web surveys service "eQuestionnaire". He subsequently became a lecturer and research assistant at the Chair for Marketing & Media Research at the Bauhaus-University of Weimar, where he completed his doctoral thesis (Dr. rer. pol.) in 2012.