FedPS: A Privacy Protection Enhanced Personalized Search Framework-Reference-Cited by-同舟云学术

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FedPS: A Privacy Protection Enhanced Personalized Search Framework

Published:2021-04-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Web Conference 2021
language:
Short-container-title:

Author:

Yao Jing¹,Dou Zhicheng²,Wen Ji-Rong³

Affiliation:

1. Renmin University of China, Beijing, China

2. Gaoling School of Artificial Intelligence and Renmin University of China, Beijing, China

3. Beijing Key Laboratory of Big Data Management and Analysis Methods and Key Laboratory of Data Engineering and Knowledge Engineering, MOE, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3442381.3449936

Reference52 articles.

1. Context Attentive Document Ranking and Query Suggestion

2. Topic Model based Privacy Protection in Personalized Web Search

Cited by 10 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. Responsible and Effective Federated Learning in Financial Services: A Comprehensive Survey;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

2. Progressive search personalization and privacy protection using federated learning;Expert Systems;2023-04-24

3. FedSH: Towards Privacy-preserving Text-based Person Re-Identification;IEEE Transactions on Multimedia;2023

4. Personalized Secure Demand-Oriented Data Service Toward Edge-Cloud Collaborative IoT;IEEE Internet of Things Journal;2023-01-01

5. Heterogeneity-Aware Adaptive Federated Learning Scheduling;2022 IEEE International Conference on Big Data (Big Data);2022-12-17

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