Reminders in Session-Based Recommender Systems: A Multi-Domain Evaluation
DOI:
https://doi.org/10.5753/isys.2026.6809Keywords:
Recommender Systems, Reminders, Session-Based Recommender SystemsAbstract
Online services expose users to vast amounts of content, leading to information overload and making it difficult to find relevant items. Recommender systems address this by personalizing user experiences based on preferences and interaction history. This work investigates Session-Based Recommender Systems (SBRS) with reminders, which reuse previously viewed items to enhance recommendation relevance. Experiments across six domains show that reminders improve performance in legal, employment, and e-commerce contexts, while having a smaller impact in music, tourism, and news, highlighting opportunities for further exploration.
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