Li Chen
Marco de Gemmis
Alexander Felfernig
Francesco Ricci
Abstract
Recommender systems have already proved to be valuable for coping with the information overload problem in several application domains. They provide people with suggestions for items which are likely to be of interest for them; hence, a primary function of recommender systems is to help people make good choices and decisions. However, most previous research has focused on recommendation techniques and algorithms, and less attention has been devoted to the decision making processes adopted by the users and possibly supported by the system. There is still a gap between the importance that the community gives to the assessment of recommendation algorithms and the current range of ongoing research activities concerning human decision making. Different decision-psychological phenomena can influence the decision making of users of recommender systems, and research along these lines is becoming increasingly important and popular. This special issue highlights how the coupling of recommendation algorithms with the understanding of human choice and decision making theory has the potential to benefit research and practice on recommender systems and to enable users to achieve a good balance between decision accuracy and decision effort.
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Index Terms
- Human Decision Making and Recommender Systems
Recommendations
RecSys'11 workshop on human decision making in recommender systems
RecSys '11: Proceedings of the fifth ACM conference on Recommender systemsInteracting with a recommender system means to take different decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera's size, zoom) as criteria, selecting feedback features to be critiqued in ...
RecSys'12 workshop on human decision making in recommender systems
RecSys '12: Proceedings of the sixth ACM conference on Recommender systemsInteracting with a recommender system means to take different decisions such as selecting an item from a recommendation list, selecting a specific item feature value (e.g., camera's size, zoom) as a search criteria, selecting feedback features to be ...
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (#IntRS)
RecSys '15: Proceedings of the 9th ACM Conference on Recommender SystemsAs an interactive intelligent system, recommender systems are developed to give recommendations that match users' preferences. Since the emergence of recommender systems, a large majority of research focuses on objective accuracy criteria and less ...
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