Measuring Recency Bias In Sequential Recommendation Systems
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917775719530496 |
|---|---|
| author | Oh, Jeonglyul Cho, Sungzoon |
| author_facet | Oh, Jeonglyul Cho, Sungzoon |
| contents | Recency bias in a sequential recommendation system refers to the overly high emphasis placed on recent items within a user session. This bias can diminish the serendipity of recommendations and hinder the system's ability to capture users' long-term interests, leading to user disengagement. We propose a simple yet effective novel metric specifically designed to quantify recency bias. Our findings also demonstrate that high recency bias measured in our proposed metric adversely impacts recommendation performance too, and mitigating it results in improved recommendation performances across all models evaluated in our experiments, thus highlighting the importance of measuring recency bias. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_09722 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Measuring Recency Bias In Sequential Recommendation Systems Oh, Jeonglyul Cho, Sungzoon Information Retrieval Machine Learning Recency bias in a sequential recommendation system refers to the overly high emphasis placed on recent items within a user session. This bias can diminish the serendipity of recommendations and hinder the system's ability to capture users' long-term interests, leading to user disengagement. We propose a simple yet effective novel metric specifically designed to quantify recency bias. Our findings also demonstrate that high recency bias measured in our proposed metric adversely impacts recommendation performance too, and mitigating it results in improved recommendation performances across all models evaluated in our experiments, thus highlighting the importance of measuring recency bias. |
| title | Measuring Recency Bias In Sequential Recommendation Systems |
| topic | Information Retrieval Machine Learning |
| url | https://arxiv.org/abs/2409.09722 |