FairCRS: Towards User-oriented Fairness in Conversational Recommendation Systems
Abstract
References
Index Terms
- FairCRS: Towards User-oriented Fairness in Conversational Recommendation Systems
Recommendations
User-oriented Fairness in Recommendation
WWW '21: Proceedings of the Web Conference 2021As a highly data-driven application, recommender systems could be affected by data bias, resulting in unfair results for different data groups, which could be a reason that affects the system performance. Therefore, it is important to identify and ...
Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users
WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data MiningIn a collaborative-filtering recommendation scenario, biases in the data will likely propagate in the learned recommendations. In this paper we focus on the so-called mainstream bias: the tendency of a recommender system to provide better ...
Conversational Collaborative Recommendation --- An Experimental Analysis
Traditionally, collaborative recommender systems have been based on a single-shot model of recommendation where a single set of recommendations is generated based on a user's (past) stored preferences. However, content-based recommender system research ...
Comments
Information & Contributors
Information
Published In

Sponsors
- SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
- SIGAI: ACM Special Interest Group on Artificial Intelligence
- SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
- SIGIR: ACM Special Interest Group on Information Retrieval
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
Conference
Acceptance Rates
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 448Total Downloads
- Downloads (Last 12 months)448
- Downloads (Last 6 weeks)46
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format