3 papers
cs.IR2019
Personalised novel and explainable matrix factorisation
Ludovik Coba, Panagiotis Symeonidis, Markus Zanker
Recommendation systems personalise suggestions to individuals to help them in their decision making and exploration tasks. In the ideal case, these recommendations, besides of bein…
cs.IR2018
Decision Making of Maximizers and Satisficers Based on Collaborative Explanations
Ludovik Coba, Markus Zanker, Laurens Rook +1
Rating-based summary statistics are ubiquitous in e-commerce, and often are crucial components in personalized recommendation mechanisms. Largely left unexplored, however, is the i…
cs.IR2018
Exploring Users' Perception of Collaborative Explanation Styles
Ludovik Coba, Markus Zanker, Laurens Rook +1
Collaborative filtering systems heavily depend on user feedback expressed in product ratings to select and rank items to recommend. In this study we explore how users value differe…