Optimizing Rankings for Recommendation in Matching Markets-Reference-Cited by-同舟云学术

Optimizing Rankings for Recommendation in Matching Markets

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2022
language:
Short-container-title:

Author:

Su Yi¹,Bayoumi Magd¹,Joachims Thorsten¹

Affiliation:

1. Cornell University, USA

Funder

NSF

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3485447.3511961

Reference46 articles.

1. Estimating Position Bias without Intrusive Interventions

2. A content based approach for recommending personnel for job positions

3. Improving Matching Process in Social Network Using Implicit and Explicit User Information

4. Itai Ashlagi Anilesh K Krishnaswamy Rahul Makhijani Daniela Saban and Kirankumar Shiragur. 2019. Assortment planning for two-sided sequential matching markets. arXiv preprint arXiv:1907.04485(2019). Itai Ashlagi Anilesh K Krishnaswamy Rahul Makhijani Daniela Saban and Kirankumar Shiragur. 2019. Assortment planning for two-sided sequential matching markets. arXiv preprint arXiv:1907.04485(2019).

5. Fairness in Recommendation Ranking through Pairwise Comparisons

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimal analysis for bandit learning in matching markets with serial dictatorship;Theoretical Computer Science;2024-09

2. Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. Scalable Job Recommendation With Lower Congestion Using Optimal Transport;IEEE Access;2024

4. The Welfare Effects of Selling Leads in a Two-Sided Marketplace;SSRN Electronic Journal;2024

5. An improved heterogeneous graph convolutional network for job recommendation;Engineering Applications of Artificial Intelligence;2023-11