| Title |
Assessing the quality of data-based explanations in recommender systems: a systematic literature review |
| Authors |
Petraitytė, Augustina ; Slotkienė, Asta |
| DOI |
10.15388/LMITT.2026.23 |
| Full Text |
|
| Is Part of |
Lietuvos magistrantų informatikos ir IT tyrimai: konferencijos darbai, 2026 m. gegužės 6 d. Vilnius.. Vilnius : Vilniaus universiteto leidykla. 2026, p. 225-235.. eISSN 2783-784X |
| Keywords [eng] |
explainable AI (XAI) ; recommender systems ; explanation quality ; user trust ; transparency ; human-centred evaluation |
| Abstract [eng] |
As recommender systems transition from “black boxes” to explainable models, assessing the quality of their explanations has become a critical research challenge. A systematic literature review has been performed to analyse how data-based explanation quality is evaluated in recent research (2021-2026). Findings reveal a significant reliance on system-oriented methods and metrics, while direct human-centred evaluation remains underrepresented. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2026 |
| CC license |
|
