Showing cs.IRShow all
2 papers · 1 filter
cs.IR2026
Exploration on Demand: From Algorithmic Control to User Empowerment
Edoardo Bianchi
Recommender systems often struggle with over-specialization, which severely limits users' exposure to diverse content and creates filter bubbles that reduce serendipitous discovery…
cs.IR2025
Beyond Relevance: An Adaptive Exploration-Based Framework for Personalized Recommendations
Edoardo Bianchi
Recommender systems must balance personalization, diversity, and robustness to cold-start scenarios to remain effective in dynamic content environments. This paper introduces an ad…