Statistical Analysis for Engineers and Scientists: A Computer-Based Approach (IBM)
Statistical Analysis for Engineers and Scientists: A Computer-Based Approach (IBM)
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
What we talk about when we talk about context
Personal and Ubiquitous Computing
An empirical investigation of decision-making satisfaction in web-based decision support systems
Decision Support Systems
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
Journal of Management Information Systems
Journal of Management Information Systems
Expert Systems with Applications: An International Journal
Experimental comparison of pre- vs. post-filtering approaches in context-aware recommender systems
Proceedings of the third ACM conference on Recommender systems
On the role of diversity in conversational recommender systems
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
Content-based recommendation systems
The adaptive web
Empirical Analysis of the Impact of Recommender Systems on Sales
Journal of Management Information Systems
Shall i trust a recommendation? towards an evaluation of the trustworthiness of recommender sites
ADBIS'09 Proceedings of the 13th East European conference on Advances in Databases and Information Systems
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques
IEEE Transactions on Knowledge and Data Engineering
A mobile 3D-GIS hybrid recommender system for tourism
Information Sciences: an International Journal
Mining large streams of user data for personalized recommendations
ACM SIGKDD Explorations Newsletter
Proceedings of the 7th ACM international conference on Web search and data mining
Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols
User Modeling and User-Adapted Interaction
Comparing context-aware recommender systems in terms of accuracy and diversity
User Modeling and User-Adapted Interaction
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Despite the growing popularity of Context-Aware Recommender Systems (CARSs), only limited work has been done on how contextual recommendations affect the behavior of customers in real-life settings. In this paper, we study the effects of contextual recommendations on the purchasing behavior of customers and their trust in the provided recommendations. In particular, we did live controlled experiments with real customers of a major commercial Italian retailer in which we compared the customers' purchasing behavior and measured their trust in the provided recommendations across the contextual, content-based and random recommendations. As a part of this study, we have investigated the role of accuracy and diversity of recommendations on customers' behavior and their trust in the provided recommendations for the three types of RSes. We have demonstrated that the context-aware RS outperformed the other two RSes in terms of accuracy, trust and other economics-based performance metrics across most of our experimental settings.