16 citations · 36 across the 5 of their papers we have counts for
5 papers
Towards a Technical Debt for Recommender System
Sergio Moreschini, Ludovik Coba, Valentina Lenarduzzi
Balancing the management of technical debt within recommender systems requires effectively juggling the introduction of new features with the ongoing maintenance and enhancement of…
Adversarial Sleeping Bandit Problems with Multiple Plays: Algorithm and Ranking Application
Jianjun Yuan, Wei Lee Woon, Ludovik Coba
This paper presents an efficient algorithm to solve the sleeping bandit with multiple plays problem in the context of an online recommendation system. The problem involves bounded,…
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…
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…
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…