Modeling User Fatigue for Sequential Recommendation
Abstract
References
Index Terms
- Modeling User Fatigue for Sequential Recommendation
Recommendations
User Popularity Preference Aware Sequential Recommendation
Computational Science – ICCS 2023AbstractIn recommender systems, users’ preferences for item popularity are diverse and dynamic, which reveals the different items that users prefer. Therefore, identifying user popularity preferences are significant for personalized recommendations. ...
User Fatigue in Online News Recommendation
WWW '16: Proceedings of the 25th International Conference on World Wide WebMany aspects and properties of Recommender Systems have been well studied in the past decade, however, the impact of User Fatigue has been mostly ignored in the literature. User fatigue represents the phenomenon that a user quickly loses the interest on ...
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling
WSDM '20: Proceedings of the 13th International Conference on Web Search and Data MiningSequential recommendation task aims to predict user preference over items in the future given user historical behaviors. The order of user behaviors implies that there are resourceful sequential patterns embedded in the behavior history which reveal the ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
- General Chairs:
- Grace Hui Yang,
- Hongning Wang,
- Sam Han,
- Program Chairs:
- Claudia Hauff,
- Guido Zuccon,
- Yi Zhang
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 279Total Downloads
- Downloads (Last 12 months)279
- Downloads (Last 6 weeks)142
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in