We propose to augment rating based recommender systems by providing the user with additional information which might help him in his choice or in the understanding of the recommen...
The more domain knowledge individual participants of a group decision process share with each other, the higher the probability of high-quality decision outcomes. In this paper we...
Alexander Felfernig, Martin Stettinger, Gerhard Le...
Location recommendation is an important feature of social network applications and location-based services. Most existing studies focus on developing one single method or model fo...
The essence of a recommender system is that it can recommend items personalized to the preferences of an individual user. But typically users are given no explicit control over th...
F. Maxwell Harper, Funing Xu, Harmanpreet Kaur, Ky...
One crucial task in recommendation is to predict what a user will buy next given her shopping history. In this paper, we propose a novel neural network to complete this task. The ...
Recommender systems research is by and large based on comparisons of recommendation algorithms’ predictive accuracies: the better the evaluation metrics (higher accuracy scores ...
The Web has grown into one of the most important channels to communicate social events nowadays. However, the sheer volume of events available in event-based social networks (EBSN...
Augusto Q. de Macedo, Leandro Balby Marinho, Rodry...
Recommender systems have become de facto tools for suggesting items that are of potential interest to users. Predicting a user’s rating on an item is the fundamental recommendat...
Large scale virtual worlds such as massive multiplayer online games or 3D worlds gained tremendous popularity over the past few years. With the large and ever increasing amount of...
Leandro Balby Marinho, Christoph Trattner, Denis P...