Abstract
Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.
Original language | English |
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Pages (from-to) | 226-247 |
Number of pages | 22 |
Journal | Asia Pacific Journal of Information Systems |
Volume | 34 |
Issue number | 1 |
DOIs | |
Publication status | Published - Mar 2024 |
Bibliographical note
Publisher Copyright:© (2024), (Korean Society of Management Information Systems). All Rights Reserved.
Keywords
- Collaborative Filtering
- Offline Evaluation
- Online Evaluation
- Recommendation Duration Effect
- Recommender Systems